Abstract 6083: Extensive epigenetic and transcriptomic donor-specific differences observed in iPSC derived allogenic NK (iNK) cells

Several autologous CAR-T cell therapies have been approved for the treatment of B cell lymphomas and leukemias and a number of trials are in progress to investigate the use of allogeneic, donor derived CAR-T and CAR-NK cell therapies for multiple tumor indications. However, sourcing cell donors, editing cells and generating large batches of clinical grade allogeneic CAR-T and CAR-NK can be challenging. To overcome these difficulties, we are developing NK and T cell-based therapies derived from induced pluripotent stem cells (iPSCs). iPSCs have the capacity to be genetically engineered, enabling precise edits that can enhance the function of cell therapies, and indefinitely expanded in culture, allowing for the production of highly uniform master cell banks. Yet, an open question of this system is the extent to which the donors’ genetic background shapes the phenotype of the iPSC-derived NK and T cells. To answer this question, we measured the genome-wide landscape of chromatin accessibility and gene expression in iNK cells generated from multiple donors. Donor background was linked to significant changes in chromatin accessibility (~30% of regions tested) and expression (~15% genes). We found accessibility changes at binding sites for transcription factors regulating various aspects of NK cell function, including differentiation (GATA2, EOMES, and ETS1), activation (AP-1, T-bet), and cytokine production (STAT3, STAT5), indicating that the donor background could impact the functionality of iPSC-derived NK cells. In particular, we noted that iNK cells derived from one donor, which had decreased effector functions compared to other cell lines, showed increased accessibility at BACH2 binding sites, a key negative regulator of NK cell function. iNK cells derived from this donor also showed an increase in expression of genes linked to NK cell differentiation and cell development, and a decrease in genes involved in cell cycle, cell proliferation, and inflammatory response pathways. Taken together, these data indicate the importance of assessing the impact of donor background on iPSC derived cell therapies through a variety of functional and genomic assays.

Citation Format: Rohith Srivas, Snehal Nariya, Melissa Rojsza, Barry A. Morse, Ohad Manor, Rupesh Amin, Luis Borges. Extensive epigenetic and transcriptomic donor-specific differences observed in iPSC derived allogenic NK (iNK) cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6083.

Environmental mismatch and obesity in humans: The Jerusalem Perinatal Family Follow-Up Study

BACKGROUND

According to the hypothesis of Gluckman and Hanson, mismatch between the developmental and postdevelopmental environments may lead to detrimental health impacts such as obesity. While several animal studies support the mismatch theory, there is a scarcity of evidence from human-based studies.

OBJECTIVES

Our study aims to examine whether a mismatch between the developmental and young-adult environments affect obesity in young adults of the Jerusalem Perinatal Family Follow-Up Study.

METHODS

Data from The Jerusalem Perinatal Family Follow-Up Study birth cohort was used to characterize early and late environments using offspring and parental sociodemographic and lifestyle information at birth, age 32 (n = 1140) and 42 (n = 404). Scores characterizing the early and late environments were constructed using factor analysis. To assess associations of mismatch with obesity, regression models were fitted using the first factor of each environment and adiposity measures at age 32 and 42.

RESULTS

Having a stable non-beneficial environment at birth and young-adulthood was most strongly associated with increased adiposity, while a stable beneficial environment was most favorable. The transition from a beneficial environment at birth to a less beneficial environment at young-adulthood was associated with higher obesity measures, including higher BMI (β = 0.979; 95% CI: 0.029, 1.929), waist circumference (β = 2.729; 95% CI: 0.317, 5.140) and waist-hip ratio (β = 0.017; 95% CI: 0.004, 0.029) compared with those experiencing a beneficial environment at both time points. Transition from a less beneficial environment at birth to a beneficial environment at adulthood was also associated with higher obesity measurements (BMI -β = 1.116; 95% CI: 0.085, 2.148; waist circumference -β = 2.736; 95% CI: 0.215, 5.256).

CONCLUSIONS

This study provides some support for the mismatch hypothesis. While there is indication that an accumulation of the effects of the non-beneficial environment has the strongest detrimental impact on obesity outcomes, our results also indicate that a mismatch between the developmental and later environments may result in maladaptation of the individual leading to obesity.

Health and disease markers correlate with gut microbiome composition across thousands of people

Variation in the human gut microbiome can reflect host lifestyle and behaviors and influence disease biomarker levels in the blood. Understanding the relationships between gut microbes and host phenotypes are critical for understanding wellness and disease. Here, we examine associations between the gut microbiota and ~150 host phenotypic features across ~3,400 individuals. We identify major axes of taxonomic variance in the gut and a putative diversity maximum along the Firmicutes-to-Bacteroidetes axis. Our analyses reveal both known and unknown associations between microbiome composition and host clinical markers and lifestyle factors, including host-microbe associations that are composition-specific. These results suggest potential opportunities for targeted interventions that alter the composition of the microbiome to improve host health. By uncovering the interrelationships between host diet and lifestyle factors, clinical blood markers, and the human gut microbiome at the population-scale, our results serve as a roadmap for future studies on host-microbe interactions and interventions.

Quality of health promotion programs is associated with built environment features in Jerusalem

Background

Neighbourhood built environment and infrastructure influence health status. Greater walkability, green spaces and healthy food accessibility can enhance healthy lifestyles. While health promotion programs (HPPs) have been shown to improve population's health, little is known about the reciprocal influences between the built environment and quality and distribution of HPPs across a city.

Methods

HPPs operating in Jerusalem focusing on healthy diet and physical activities were located and evaluated for quality using the European Quality Instrument for Health Promotion (EQUIHP) in 2017. HPPs location, intervention type and characteristics of the target population were documented. Using Geographic Information System (GIS), we combined infrastructure data from the Jerusalem Municipality and socioeconomic score (1 lowest - 10 highest) from Israel's Central Bureau of Statistics. Associations between distribution and quality of HPPs and the built environment at the neighbourhood (n = 115) level and municipal planning area level (7 areas) were assessed.

Results

Overall 93 HPPs operating in 349 locations and serving 582,500 adult residents, were identified in Jerusalem. Higher HPP quality, at the municipal planning area, was associated with higher density of HPPs, longer bike or walking lanes and fewer food stores. Positive significant (p < 0.05) correlations, at a neighbourhood level, were found between neighbourhood EQUIHP median scores and HPPs targeting women (0.262), participants < 60 years old (0.324) and the Arab ethnicity (0.473). Linear regression showed a significant (p = 0.01) decrease of 0.015 in median EQUIHP score at a neighbourhood level for each increase in socioeconomic status score (p = 0.036).

Conclusions

A comprehensive evaluation of HPP quality, spatial and sociodemographic information demonstrates an association of HPP access and quality with the built environment. Fortunately, in Jerusalem high quality programs are designed for populations at need.

Key messages

In Jerusalem, the quality of health promotion programs measured by the EQUIHP score, was positively associated with infrastructure features promoting physical activity and lower neighbourhood SES. In Jerusalem, higher quality of health promotion programs focusing in nutrition and physical activity were designed for populations at need.

Abstract 729: Landscape of homologous recombination repair (HRR) mutations in prostate cancer profiled by ctDNA next-generation sequencing

Background: PARP inhibition can cause synthetic lethality and increased therapeutic sensitivity in patients with HRR deficiency (HRD), which can be detected through the molecular profiling of HRR genes. Prostate cancer has a high prevalence of HRD (20-25%, Athie 2019). High failure rates for tissue biopsy in metastatic prostate cancer patients (25-75%) (Ross 2005, Spritzer 2013) pose challenges for HRD profiling, underscoring the need for a non-invasive, ctDNA alternative. Copy number loss, a frequent cause of HRD, is further difficult to call due to signal dilution by cell-free leukocytic DNA. We developed a pipeline that detects loss-of-function SNV/Indels, structural rearrangements, and gene deletions to identify HRD on GuardantOMNITM, a 500-gene liquid biopsy panel. We present its performance across >620 prostate cancer GuardantOMNITM samples.

Methods: Samples from 627 prostate cancer patients were processed on GuardantOMNITM RUO, with median unique coverage of 4982 molecules sequenced to 20,000x read depth. Somatic and germline SNVs and small indels were called using the Guardant bioinformatics pipeline (Helman 2018). A novel HRD module was developed to annotate pathogenic SNV/Indels and identify structural rearrangements, gene-level homozygous deletions, loss-of-heterozygosity (LOH) and genome-wide LOH, comprising of a novel CNV (Barbacioru 2019) and de-novo fusion caller (Gnerre, submitted). Loss-of-function variants were analyzed in 24 HRD genes.

Results: Pathogenic alterations in HRD genes were called in 260/620 (42%) prostate cancer samples with ctDNA detected: 28% of all samples had a pathogenic somatic or germline SNV/Indel, 20% had a homozygous deletion, 3.4% had a rearrangement involving an HRD gene. The majority of SNV/Indels occurred in BRCA2 (31% of all 158 SNV/Indels) and ATM (22%), similar to tissue (Dahwan 2016), but mutations also occurred across an additional 21 genes, including CDK12 (8%), CHEK2 (5%) and NBN (3.8%). Of prostate patients with a germline BRCA1/2 SNV/Indel and sufficient tumor shedding for LOH detection (max MAF>10%), 10/19 (52%) also had LOH, compared to 86% in tissue (Jonsson 2019). Homozygous deletions were enriched in BRCA2 (6.9% of all samples), ATM (4.4%) and CHEK1 (2.3%). Rearrangements, including fusions and multi-exonic deletions, accounted for 6.5% of inactivating HRD mutations detected. In total, 24% of prostate samples had a biallelic inactivation involving an SNV, Indel or deletion.

Conclusion: We demonstrate in a prostate cancer cohort that GuardantOMNITM ctDNA profiling calls all classes of mutations contributing to HRD, with relative prevalence of alterations consistent with those in tissue. CfDNA presents a potential alternative for identifying patients who may benefit from PARP or cisplatin/platinum therapies, expanding the prevalence from 28% using small variants to 42% with the complete HRD biomarker set.

Citation Format: Jennifer Yen, Sante Gnerre, Catalin Barbacioru, Elena Helman, Ohad Manor, Arielle Yablonovitch, Ravi Vijaya Satya, Leo Liu, Jennifer Saam, Stephen Fairclough, Becky Nagy, Richard Lanman, Darya Chudova, AmirAli Talasaz. Landscape of homologous recombination repair (HRR) mutations in prostate cancer profiled by ctDNA next-generation sequencing [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 729.

A Multi-omic Association Study of Trimethylamine N-Oxide

Trimethylamine N-oxide (TMAO) is a circulating metabolite that has been implicated in the development of atherosclerosis and cardiovascular disease (CVD). In this paper, we identify blood markers, metabolites, proteins, gut microbiota patterns, and diets that are significantly associated with levels of plasma TMAO. We find that kidney markers are strongly associated with TMAO and identify CVD-related proteins that are positively correlated with TMAO. We show that metabolites derived by the gut microbiota are strongly correlated with TMAO and that the magnitude of this correlation varies with kidney function. Moreover, we identify diet-associated patterns in the microbiome that are correlated with TMAO. These findings suggest that both the process of TMAO accumulation and the mechanism by which TMAO promotes atherosclerosis are a complex interplay between diet and the microbiome on one hand and other system-level factors such as circulating proteins, metabolites, and kidney function.

Diabetes care in individuals with severe mental Illnesses in Israel

Background

Cardiovascular disease and risk factors are more common in people with severe mental illness (SMI; schizophrenia, schizoaffective disorders, and bi-polar disorders). For instance, diabetes mellitus (DM) prevalence was reported to be 2-3 times higher, with higher incidence and severity of complications. In 2015, following a reform in mental health services in Israel, services were transferred to the responsibility of the health plans, allowing a comprehensive healthcare. We aimed to compare quality of care indicators and intermediate DM outcomes in individuals with SMI compared to the general population.

Methods

The Israel national program for quality indicators in community healthcare obtains data from electronic medical records from the four health plans, covering the entire civilian population. In 2017, n = 74,226 individuals aged ≥18 years had a registered diagnosis of SMI (prevalence 1.37%). DM prevalence, hemoglobin A1c (HbA1c) testing yearly, and DM control in individuals with SMI were compared with the general population.

Results

DM prevalence in adults with SMI in 2017 was 14.3%, compared with 9.7% among all Israeli adults (RR of 1.5). rates of HbA1c testing and control (HbA1c<7-8%, depending on age and duration of disease) were similar among DM patients with SMI and the general population (testing: 90.1% and 90.9%; Control: 70.8% and 69.7%, SMI and general population, respectively); Similarly, uncontrolled DM (HbA1c>9%) was observed in 10.8% of individuals with SMI and in 10.0% of the general population.

Conclusions

Along with the expected excess of DM prevalence in individuals with SMI, quality of care DM indicators rates were alike among those with SMI as in the general population, suggesting non-inferior quality of care. This is consistent with results reported by the British national diabetes audit for England and Wales. However, our results are limited by a possible under-registration or diagnosis of SMI in the Israeli population.

Key messages

Higher diabetes mellitus prevalence is observed in individuals with severe mental illness. Hemoglobin A1c testing and diabetes mellitus control rates are alike in individuals with severe mental illness compared with the general population, suggesting non-inferior quality of care.

Diabetes in Israel- do all patients receive equal care?

Background

Diabetes Mellitus (DM) is associated with micro- and macro-vascular complications, leading to high burden of morbidity and mortality. Populations of low socioeconomic position (SEP) in various countries were found to have increased prevalence of the disease, worse glycemic control, and increased complications. We aimed to examine whether there are social disparities in diabetes care in Israel, as reflected in a national program for quality indicators.

Methods

The Israel National Program for Quality Indicators in Community Healthcare obtains data from electronic medical records from all health plans, covering the entire Israeli population. In 2017, 497,397 individuals aged >18 years were identified with DM. DM prevalence, quality of care indicators, including process and intermediate outcomes were explored by SEP categories (1-10), determined according to residential addresses.

Results

DM prevalence in Israeli adults in 2017 was 9.7%, showing a strong SEP gradient, with higher prevalence in individuals of lower SEP. No SEP disparities were observed in process indicators with overall rates of documentation of hemoglobin A1c (HbA1c) of 90.9%, ophthalmologic examinations of 72.5%, and kidney function examinations of 92.5%. However, strong SEP disparities were observed in the prevalence of uncontrolled diabetes (HbA1c≥9%), with an overall rate of 10.0%, and a 5.4-times higher rate in diabetics of the lowest SES level (23.5%) compared with the highest SEP level (4.3%). A somewhat weaker gradient was seen for the well-control of DM (HbA1c<7-8%, according to duration of disease and age), with an overall rate of 69.7%, and a 1.7 ratio, comparing diabetics of the highest vs the lowest SEP level.

Conclusions

These findings suggest that access to care does not explain SEP disparities in diabetes control in Israel. There is a need to explore the underlying social, cultural, and possibly the benefits-policy determinants of poor control among individuals of low SEP.

Key messages

Wide socioeconomic disparities are present among Israeli adults in diabetes mellitus prevalence and control rates, but not in care processes indicators. These findings call for a deeper understanding of the determinants and perhaps a revision of current social benefits policy, which may encourage lack of glycemic control.

Socioeconomic disparities in diabetes prevalence and quality of care among Israeli children

Background

Despite Israel’s universal health coverage, disparities in health services provision may still exist. We aimed to assess socioeconomic disparities in diabetes prevalence and quality of care among Israeli children, and to assess trends in these over time.

Methods

Repeated cross-sectional analyses in the setting of the National Program for Quality Indicators in Community Healthcare that receives data based on electronic medical records from Israel’s four health maintenance organizations. The study population included all Israeli children aged 2-19 years in 2011-2017 (for 2017: N = 2,364,374, including 2,914 with diabetes). Socio-economic position (SEP) was measured using Central Bureau of Statistics data further updated by a private company (Points Business Mapping Ltd), and grouped into 4 categories, ranging from 1 (lowest) to 4 (highest). Using logistic regression, we assessed the association of SEP with diabetes prevalence, diabetes clinic visits, hemoglobin A1C (HbA1C) testing, and poor glycemic control (HbA1C> 9%), and assessed whether these changed over time. Models were adjusted for age, and sex.

Results

Diabetes prevalence increased with age and SEP. SEP was positively associated with visiting a specialized diabetes clinic (OR SEP 4 vs. 1 2.53, 95% CI 1.72 - 3.70). Odds of HbA1C testing and odds of poor glycemic control were negatively associated with SEP (OR SEP 4 vs. 1: 0.54, 95% CI 0.40 - 0.72 and OR SEP 4 vs. 1: 0.25, 95% CI 0.18 - 0.34 respectively). Disparities were especially apparent among children aged 2-9 (4.6% poor glycemic control in SEP 4 vs. 40.8% in SEP 1). Poor glycemic control decreased over time, from 44.0% in 2011 to 34.8% in 2017.

Conclusions

While poor glycemic control rates among children have improved, significant socioeconomic gaps remain. It is eminent to study the causes of these disparities and develop policies to improve care provided to children in the lower SEP levels, to promote health equity.

Key messages

Major socioeconomic inequalities in the control of diabetes among children in Israel remain despite universal health care coverage. The rate of uncontrolled diabetes among Israeli children has improved over time.

Blood metabolome predicts gut microbiome α-diversity in humans

Depleted gut microbiome α-diversity is associated with several human diseases, but the extent to which this is reflected in the host molecular phenotype is poorly understood. We attempted to predict gut microbiome α-diversity from ~1,000 blood analytes (laboratory tests, proteomics and metabolomics) in a cohort enrolled in a consumer wellness program (N = 399). Although 77 standard clinical laboratory tests and 263 plasma proteins could not accurately predict gut α-diversity, we found that 45% of the variance in α-diversity was explained by a subset of 40 plasma metabolites (13 of the 40 of microbial origin). The prediction capacity of these 40 metabolites was confirmed in a separate validation cohort (N = 540) and across disease states, showing that our findings are robust. Several of the metabolite biomarkers that are reported here are linked with cardiovascular disease, diabetes and kidney function. Associations between host metabolites and gut microbiome α-diversity were modified in those with extreme obesity (body mass index ≥ 35), suggesting metabolic perturbation. The ability of the blood metabolome to predict gut microbiome α-diversity could pave the way to the development of clinical tests for monitoring gut microbial health.

Habitual sleep duration and sleep duration variation are independently associated with body mass index

BACKGROUND

Sleep plays a vital role in maintaining homeostasis and promoting health. Previous studies show that shorter sleep duration is associated with elevated body mass index (BMI) and other cardiovascular risk factors. The goal of this study was to investigate the effects of habitual sleep duration and nightly sleep duration variation based on daily device-recorded data on BMI and obesity-related biomarkers.

METHODS

In all, 748 individuals (50.6% females, 85.4% European-Americans, average age: 49.7 years old) participated in a commercial lifestyle coaching program beginning in July 2015. Daily sleep data were recorded by Fitbit Charge HR wristbands. Clinical laboratory blood tests were measured up to three times over a 12-month period. Linear regression models were used for cross-sectional analyses, and generalized estimating equations for longitudinal analyses. All models were adjusted for age, sex, geographic location, season, genetic ancestry inferred from whole genome sequencing data, and BMI (if applicable). Multiple testing issues were corrected by false discovery rate.

RESULTS

We calculated habitual sleep duration and nightly sleep duration variation. In general, females slept 15-min longer on average than males. A negative correlation was found between habitual sleep duration and BMI (β=-1.12, standard error=0.25, P<0.001). Moreover, we identified a positive correlation between sleep duration variation and BMI (β=2.97, standard error=0.79, P<0.001) while controlling for sleep duration, indicating that larger sleep duration variation is significantly and independently associated with increased BMI.

CONCLUSIONS

We explored the impact of habitual sleep duration and sleep duration variation, and identified that shorter habitual sleep duration and larger duration variation were independently associated with increased BMI.

Live birth sex ratios and father's geographic origins in Jerusalem, 1964-1976

OBJECTIVE

To examine whether ancestry influenced sex ratios of offspring in a birth cohort before parental antenatal sex selection influenced offspring sex.

METHODS

We measured the sex ratio as the percent of males according to countries of birth of paternal and maternal grandfathers in 91,459 live births from 1964 to 1976 in the Jerusalem Perinatal Study. Confidence limits (CI) were computed based on an expected sex ratio of 1.05, which is 51.4% male.

RESULTS

Of all live births recorded, 51.4% were male. Relative to Jewish ancestry (51.4% males), significantly more males (1,761) were born to Muslim ancestry (54.5, 95% CI = 52.1-56.8, P = 0.01). Among the former, sex ratios were not significantly associated with paternal or maternal age, education, or offspring's birth order. Consistent with a preference for male offspring, the sex ratio decreased despite increasing numbers of births over the 13-year period. Sex ratios were not affected by maternal or paternal origins in North Africa or Europe. However, the offspring whose paternal grandfathers were born in Western Asia included fewer males than expected (50.7, 50.1-51.3, P = 0.02), whether the father was born abroad (50.7) or in Israel (50.8). This was observed for descendents of paternal grandfathers born in Lebanon (47.6), Turkey (49.9), Yemen & Aden (50.2), Iraq (50.5), Afghanistan (50.5), Syria (50.6), and Cyprus (50.7); but not for those from India (51.5) or Iran (51.9). The West Asian group showed the strongest decline in sex ratios with increasing paternal family size.

CONCLUSIONS

A decreased sex ratio associated with ancestry in Western Asia is consistent with reduced ability to bear sons by a subset of Jewish men in the Jerusalem cohort. Lower sex ratios may be because of pregnancy stress, which may be higher in this subgroup. Alternatively, a degrading Y chromosome haplogroup or other genetic or epigenetic differences on male germ lines could affect birth ratios, such as differential exposure to an environmental agent, dietary differences, or stress. Differential stopping behaviors that favor additional pregnancies following the birth of a daughter might exacerbate these lower sex ratios.

Systematic Characterization and Analysis of the Taxonomic Drivers of Functional Shifts in the Human Microbiome

Comparative analyses of the human microbiome have identified both taxonomic and functional shifts that are associated with numerous diseases. To date, however, microbiome taxonomy and function have mostly been studied independently and the taxonomic drivers of functional imbalances have not been systematically identified. Here, we present FishTaco, an analytical and computational framework that integrates taxonomic and functional comparative analyses to accurately quantify taxon-level contributions to disease-associated functional shifts. Applying FishTaco to several large-scale metagenomic cohorts, we show that shifts in the microbiome's functional capacity can be traced back to specific taxa. Furthermore, the set of taxa driving functional shifts and their contribution levels vary markedly between functions. We additionally find that similar functional imbalances in different diseases are driven by both disease-specific and shared taxa. Such integrated analysis of microbiome ecological and functional dynamics can inform future microbiome-based therapy, pinpointing putative intervention targets for manipulating the microbiome's functional capacity.

Revised computational metagenomic processing uncovers hidden and biologically meaningful functional variation in the human microbiome

BACKGROUND

Recent metagenomic analyses of the human gut microbiome identified striking variability in its taxonomic composition across individuals. Notably, however, these studies often reported marked functional uniformity, with relatively little variation in the microbiome's gene composition or in its overall metabolic capacity.

RESULTS

Here, we address this surprising discrepancy between taxonomic and functional variations and set out to track its origins. Specifically, we demonstrate that the functional uniformity observed in microbiome studies can be attributed, at least partly, to common computational metagenomic processing procedures that mask true functional variation across microbiome samples. We identify several such procedures, including commonly used practices for gene abundance normalization, mapping of gene families to functional pathways, and gene family aggregation. We show that accounting for these factors and using revised metagenomic processing procedures uncovers such hidden functional variation, significantly increasing observed variation in the abundance of functional elements across samples. Importantly, we find that this uncovered variation is biologically meaningful and that it is associated with both host identity and health.

CONCLUSIONS

Accurate characterization of functional variation in the microbiome is essential for comparative metagenomic analyses in health and disease. Our finding that metagenomic processing procedures mask underlying and biologically meaningful functional variation therefore highlights an important challenge such studies may face. Alternative schemes for metagenomic processing that uncover this hidden functional variation can facilitate improved metagenomic analysis and help pinpoint disease- and host-associated shifts in the microbiome's functional capacity.

Microbiome sharing between children, livestock and household surfaces in western Kenya

The gut microbiome community structure and development are associated with several health outcomes in young children. To determine the household influences of gut microbiome structure, we assessed microbial sharing within households in western Kenya by sequencing 16S rRNA libraries of fecal samples from children and cattle, cloacal swabs from chickens, and swabs of household surfaces. Among the 156 households studied, children within the same household significantly shared their gut microbiome with each other, although we did not find significant sharing of gut microbiome across host species or household surfaces. Higher gut microbiome diversity among children was associated with lower wealth status and involvement in livestock feeding chores. Although more research is necessary to identify further drivers of microbiota development, these results suggest that the household should be considered as a unit. Livestock activities, health and microbiome perturbations among an individual child may have implications for other children in the household.

Associations of socioeconomic position in childhood and young adulthood with cardiometabolic risk factors: the Jerusalem Perinatal Family Follow-Up Study

BACKGROUND

Several stages in the life course have been identified as important to the development of cardiovascular disease. This study aimed to assess the associations of childhood and adulthood socioeconomic position (SEP) and social mobility with cardiometabolic risk factors (CMRs) later in life.

METHODS

We conducted follow-up examinations of 1132 offspring, aged 32, within a population-based cohort of all births in Jerusalem from 1974 to 1976. SEP was indicated by parents' occupation and education, and adulthood SEP was based on offspring's occupation and education recorded at age 32. Linear regression models were used to investigate the associations of SEP and social mobility with CMRs.

RESULTS

Childhood-occupational SEP was negatively associated with body mass index (BMI; β=-0.29, p=0.031), fat percentage (fat%; β=-0.58, p=0.005), insulin (β=-0.01, p=0.031), triglycerides (β=-0.02, p=0.024) and low-density lipoprotein cholesterol (LDL-C; β=-1.91, p=0.015), independent of adulthood SEP. Adulthood-occupational SEP was negatively associated with waist-to-hip ratio (WHR; β=-0.01, p=0.002), and positively with high-density lipoprotein cholesterol (HDL-C; β=0.87, p=0.030). Results remained similar after adjustment for smoking and inactivity. Childhood-educational SEP was associated with decreased WHR and LDL-C level (p=0.0002), and adulthood-educational SEP was inversely associated with BMI (p=0.001), waist circumference (p=0.008), WHR (p=0.001) and fat% (p=0.0002) and positively associated with HDL-C (p=0.030). Additionally, social mobility (mainly upward) was shown to have adverse cardiometabolic outcomes.

CONCLUSIONS

Both childhood and adulthood SEP contribute independently to CMR. The match-mismatch hypothesis may explain the elevated CMRs among participants experiencing social mobility. Identification of life-course SEP-related aspects that translate into social inequality in cardiovascular risk may facilitate efforts for improving health and for reducing disparities in cardiovascular disease.

Publication metrics and success on the academic job market

The number of applicants vastly outnumbers the available academic faculty positions. What makes a successful academic job market candidate is the subject of much current discussion [1-4]. Yet, so far there has been no quantitative analysis of who becomes a principal investigator (PI). We here use a machine-learning approach to predict who becomes a PI, based on data from over 25,000 scientists in PubMed. We show that success in academia is predictable. It depends on the number of publications, the impact factor (IF) of the journals in which those papers are published, and the number of papers that receive more citations than average for the journal in which they were published (citations/IF). However, both the scientist's gender and the rank of their university are also of importance, suggesting that non-publication features play a statistically significant role in the academic hiring process. Our model (www.pipredictor.com) allows anyone to calculate their likelihood of becoming a PI.

MUSiCC: a marker genes based framework for metagenomic normalization and accurate profiling of gene abundances in the microbiome

Functional metagenomic analyses commonly involve a normalization step, where measured levels of genes or pathways are converted into relative abundances. Here, we demonstrate that this normalization scheme introduces marked biases both across and within human microbiome samples, and identify sample- and gene-specific properties that contribute to these biases. We introduce an alternative normalization paradigm, MUSiCC, which combines universal single-copy genes with machine learning methods to correct these biases and to obtain an accurate and biologically meaningful measure of gene abundances. Finally, we demonstrate that MUSiCC significantly improves downstream discovery of functional shifts in the microbiome.

MUSiCC is available at http://elbo.gs.washington.edu/software.html.

GenoExp: a web tool for predicting gene expression levels from single nucleotide polymorphisms

Understanding the effect of single nucleotide polymorphisms (SNPs) on the expression level of genes is an important goal. We recently published a study in which we devised a multi-SNP predictive model for gene expression in Lymphoblastoid cell lines (LCL), and showed that it can robustly predict the expression of a small number of genes in test individuals. Here, we validate the generality of our models by predicting expression profiles for genes in LCL in an independent study, and extend the pool of predictable genes for which we are able to explain more than 25% of their expression variability to 232 genes across 14 different cell types. As the number of people who obtained their SNP profiles through companies such as 23andMe is rising rapidly, we developed GenoExp, a web-based tool in which users can upload their individual SNP data and obtain predicted expression levels for the set of predictable genes across the 14 different cell types. Our tool thus allows users with biological knowledge to study the possible effects that their set of SNPs might have on these genes and predict their cell-specific expression levels relative to the population average.

AVAILABILITY AND IMPLEMENTATION

GenoExp is freely available at http://genie.weizmann.ac.il/pubs/GenoExp/.

Mapping the inner workings of the microbiome: genomic- and metagenomic-based study of metabolism and metabolic interactions in the human microbiome

The human gut microbiome is a major contributor to human metabolism and health, yet the metabolic processes that are carried out by various community members, the way these members interact with each other and with the host, and the impact of such interactions on the overall metabolic machinery of the microbiome have not yet been mapped. Here, we discuss recent efforts to study the metabolic inner workings of this complex ecosystem. We will specifically highlight two interrelated lines of work, the first aiming to deconvolve the microbiome and to characterize the metabolic capacity of various microbiome species and the second aiming to utilize computational modeling to infer and study metabolic interactions between these species.

Probing the effect of promoters on noise in gene expression using thousands of designed sequences

Genetically identical cells exhibit large variability (noise) in gene expression, with important consequences for cellular function. Although the amount of noise decreases with and is thus partly determined by the mean expression level, the extent to which different promoter sequences can deviate away from this trend is not fully known. Here, we present a high-throughput method for measuring promoter-driven noise for thousands of designed synthetic promoters in parallel. We use it to investigate how promoters encode different noise levels and find that the noise levels of promoters with similar mean expression levels can vary more than one order of magnitude, with nucleosome-disfavoring sequences resulting in lower noise and more transcription factor binding sites resulting in higher noise. We propose a kinetic model of gene expression that takes into account the nonspecific DNA binding and one-dimensional sliding along the DNA, which occurs when transcription factors search for their target sites. We show that this assumption can improve the prediction of the mean-independent component of expression noise for our designed promoter sequences, suggesting that a transcription factor target search may affect gene expression noise. Consistent with our findings in designed promoters, we find that binding-site multiplicity in native promoters is associated with higher expression noise. Overall, our results demonstrate that small changes in promoter DNA sequence can tune noise levels in a manner that is predictable and partly decoupled from effects on the mean expression levels. These insights may assist in designing promoters with desired noise levels.

Multifaceted activities of type I interferon are revealed by a receptor antagonist

Type I interferons (IFNs), including various IFN-α isoforms and IFN-β, are a family of homologous, multifunctional cytokines. IFNs activate different cellular responses by binding to a common receptor that consists of two subunits, IFNAR1 and IFNAR2. In addition to stimulating antiviral responses, they also inhibit cell proliferation and modulate other immune responses. We characterized various IFNs, including a mutant IFN-α2 (IFN-1ant) that bound tightly to IFNAR2 but had markedly reduced binding to IFNAR1. Whereas IFN-1ant stimulated antiviral activity in a range of cell lines, it failed to elicit immunomodulatory and antiproliferative activities. The antiviral activities of the various IFNs tested depended on a set of IFN-sensitive genes (the "robust" genes) that were controlled by canonical IFN response elements and responded at low concentrations of IFNs. Conversely, these elements were not found in the promoters of genes required for the antiproliferative responses of IFNs (the "tunable" genes). The extent of expression of tunable genes was cell type-specific and correlated with the magnitude of the antiproliferative effects of the various IFNs. Although IFN-1ant induced the expression of robust genes similarly in five different cell lines, its antiviral activity was virus- and cell type-specific. Our findings suggest that IFN-1ant may be a therapeutic candidate for the treatment of specific viral infections without inducing the immunomodulatory and antiproliferative functions of wild-type IFN.

Landscape and variation of RNA secondary structure across the human transcriptome

In parallel to the genetic code for protein synthesis, a second layer of information is embedded in all RNA transcripts in the form of RNA structure. RNA structure influences practically every step in the gene expression program¹. Yet the nature of most RNA structures or effects of sequence variation on structure are not known. Here we report the initial landscape and variation of RNA secondary structures (RSS) in a human family Trio, providing a comprehensive RSS map of human coding and noncoding RNAs. We identify unique RSS signatures that demarcate open reading frames, splicing junctions, and define authentic microRNA binding sites. Comparison of native deproteinized RNA isolated from cells versus refolded purified RNA suggests that the majority of the RSS information is encoded within RNA sequence. Over 1900 transcribed single nucleotide variants (~15% of all transcribed SNVs) alter local RNA structure. We discover simple sequence and spacing rules that determine the ability of point mutations to impact RSS. Selective depletion of RiboSNitches versus structurally synonymous variants at precise locations suggests selection for specific RNA shapes at thousands of sites, including 3’UTRs, binding sites of miRNAs and RNA binding proteins genome-wide. These results highlight the potentially broad contribution of RNA structure and its variation to gene regulation.

Predicting disease risk using bootstrap ranking and classification algorithms

Genome-wide association studies (GWAS) are widely used to search for genetic loci that underlie human disease. Another goal is to predict disease risk for different individuals given their genetic sequence. Such predictions could either be used as a “black box” in order to promote changes in life-style and screening for early diagnosis, or as a model that can be studied to better understand the mechanism of the disease. Current methods for risk prediction typically rank single nucleotide polymorphisms (SNPs) by the p-value of their association with the disease, and use the top-associated SNPs as input to a classification algorithm. However, the predictive power of such methods is relatively poor. To improve the predictive power, we devised BootRank, which uses bootstrapping in order to obtain a robust prioritization of SNPs for use in predictive models. We show that BootRank improves the ability to predict disease risk of unseen individuals in the Wellcome Trust Case Control Consortium (WTCCC) data and results in a more robust set of SNPs and a larger number of enriched pathways being associated with the different diseases. Finally, we show that combining BootRank with seven different classification algorithms improves performance compared to previous studies that used the WTCCC data. Notably, diseases for which BootRank results in the largest improvements were recently shown to have more heritability than previously thought, likely due to contributions from variants with low minimum allele frequency (MAF), suggesting that BootRank can be beneficial in cases where SNPs affecting the disease are poorly tagged or have low MAF. Overall, our results show that improving disease risk prediction from genotypic information may be a tangible goal, with potential implications for personalized disease screening and treatment.

Genome-wide association studies are widely used to search for genetic loci that underlie human disease. Another goal is to predict disease risk for different individuals given their genetic sequence. Such predictions could either be used as a “black box” in order to promote changes in life-style and screening for early diagnosis, or as a model that can be studied to better understand the mechanism of the disease. Current methods for risk prediction have relatively poor performance, with one possible explanation being the fact they rely on a noisy ranking of genetic variants given to them as input. To improve the predictive power, we devised BootRank, a ranking method less sensitive to noise. We show that BootRank improves the ability to predict disease risk of unseen individuals in the Wellcome Trust Case Control Consortium (WTCCC) data, and that combining BootRank with different classification algorithms improves performance compared to previous studies that used these data. Overall, our results show that improving disease risk prediction from genotypic information may be a tangible goal, with potential implications for personalized disease screening and treatment.

Robust prediction of expression differences among human individuals using only genotype information

Many genetic variants that are significantly correlated to gene expression changes across human individuals have been identified, but the ability of these variants to predict expression of unseen individuals has rarely been evaluated. Here, we devise an algorithm that, given training expression and genotype data for a set of individuals, predicts the expression of genes of unseen test individuals given only their genotype in the local genomic vicinity of the predicted gene. Notably, the resulting predictions are remarkably robust in that they agree well between the training and test sets, even when the training and test sets consist of individuals from distinct populations. Thus, although the overall number of genes that can be predicted is relatively small, as expected from our choice to ignore effects such as environmental factors and trans sequence variation, the robust nature of the predictions means that the identity and quantitative degree to which genes can be predicted is known in advance. We also present an extension that incorporates heterogeneous types of genomic annotations to differentially weigh the importance of the various genetic variants, and we show that assigning higher weights to variants with particular annotations such as proximity to genes and high regional G/C content can further improve the predictions. Finally, genes that are successfully predicted have, on average, higher expression and more variability across individuals, providing insight into the characteristics of the types of genes that can be predicted from their cis genetic variation.

Variation in gene expression across different individuals has been found to play a role in susceptibility to different diseases. In addition, many genetic variants that are linked to changes in expression have been found to date. However, their joint ability to accurately predict these changes is not well understood and has rarely been evaluated. Here, we devise a method that uses multiple genetic variants to explain the variation in expression of genes across individuals. One important aspect of our method is its robustness, in that our predictions agree well between training and test sets. Thus, although the number of genes that could be explained is relatively small, the identity and quantitative degree to which genes can be predicted is known in advance. We also present an extension to our method that integrates different genomic annotations such as location of the genetic variant or its context to differentially weigh the genetic variants in our model and improve predictions. Finally, genes that are successfully predicted have, on average, higher expression and more variability across individuals, providing insight into the characteristics of the types of genes that can be predicted by our method.

Sex differences in risk factors for coronary artery disease and stroke in men and women aged 45-65 years

BACKGROUND

Coronary artery disease (CAD) and stroke both result from atherosclerosis. Risk factor profiles for CAD and stroke have been reported to differ between middle-aged men and women.

OBJECTIVE

To compare, for men and women aged 45-65 years, between risk factor profiles for CAD and stroke.

METHODS

This is a retrospective study based on the medical records of 179 women and 270 men diagnosed with CAD, and 114 women and 190 men diagnosed with stroke, hospitalised in one of two medical centres in Jerusalem. We assessed and compared the number of metabolic risk factors (diabetes, hypertension and hypercholesterolaemia) presenting among men and women between the CAD and stroke groups.

RESULTS

Among patients with CAD, significantly more women than men presented with diabetes, hypertension and hypercholesterolaemia. In contrast, no statistically significant differences were observed between genders in the prevalence of diabetes, hypertension and hypercholesterolaemia among the stroke patients. Hypertension was more prevalent in both men and women among stroke patients than CAD patients. In the stroke group, 29.1% of the women compared with 14.2% of the men presented with the three metabolic risk factors investigated.

CONCLUSIONS

In a middle-aged population, CAD risk factor profiles differed between genders while stroke risk factor profiles did not.

FC21-06 - Schizophrenia after the 1941 farhud (a pogrom in IRAQ); a study of 6,781 IRAQI-born men and women observed as parents in the jerusalem cohort

Introduction

Maternal stress during pregnancy has been associated with schizophrenia in some settings with evidence suggesting that male and female offspring might be affected differently.

Objectives/aims

In an outbreak of violence in 1941, at least 180 Jews died in Baghdad; rapes, beatings and property damage injured hundreds more in other towns. We questioned whether this stress might be reflected in any change in schizophrenia incidence in people born in 1941.

Methods

We studied admissions to psychiatric hospitals in 39,606 men and 41,208 women, parents of the population-based Jerusalem cohort. We used proportional hazards models to estimate relative incidence of schizophrenia in various groups, over time. Subjects were followed from age in 1950 or immigration, till age at first hospital admission, death or 2004. Schizophrenia was defined by discharge diagnosis, ICD-10 = F20–F29 at any hospital event. Models controlled for secular and cyclic time trends.

Results

For all years combined, the 3,679 male immigrants from Iraq showed a schizophrenia incidence similar to other men (relative risk RR = 0.92, 95% confidence limits 0.67–1.26). But for 141 men born in Iraq in 1941, RR = 4.12 (1.67–10.2, p = .0021 based on 6 cases), compared with men from Iraq born in all other years. Among other men, RR for 1941 births was 1.21 (0.78–1.88,). Women from Iraq showed no significant findings.

Conclusions

These findings enlarge on long-term consequences of ethnic violence. They raise intriguing questions about the relative resilience of the sexes, but should be interpreted cautiously, given that all subjects in this cohort had been able to reproduce.

Age, sex and first treatment of schizophrenia in a population cohort

OBJECTIVE

Schizophrenia affects men more than women, but this may not be true at all ages. This study examines the incidence of first hospitalization for treatment of schizophrenia in each sex over different ages.

METHODS

We compared the incidence of first admission for treatment in a cohort of 46,388 males and 43,680 females followed from birth until ages 29-41, using life tables and proportional hazards methods.

RESULTS

Life table estimates of cumulative incidence by age 40 were 1.44% in males and 0.86% in females. For over all ages the relative risk (RR) in males was 1.6 (95% confidence limits=1.4-1.8) compared with females. Before age 17 there was no significant difference between the sexes (RR=0.86, 0.56-1.3). Excess risk in males was observed only from age 17 (RR=1.7, 1.4-1.9). There was no evidence of the incidence in females catching up with that in males, during the 30s.

CONCLUSION

In this population, there was a significant change, over age, in the relative incidence of first hospitalization for schizophrenia between the sexes; the excess incidence in males first developed at age 17.

Long noncoding RNA as modular scaffold of histone modification complexes

Long intergenic noncoding RNAs (lincRNAs) regulate chromatin states and epigenetic inheritance. Here, we show that the lincRNA HOTAIR serves as a scaffold for at least two distinct histone modification complexes. A 5' domain of HOTAIR binds polycomb repressive complex 2 (PRC2), whereas a 3' domain of HOTAIR binds the LSD1/CoREST/REST complex. The ability to tether two distinct complexes enables RNA-mediated assembly of PRC2 and LSD1 and coordinates targeting of PRC2 and LSD1 to chromatin for coupled histone H3 lysine 27 methylation and lysine 4 demethylation. Our results suggest that lincRNAs may serve as scaffolds by providing binding surfaces to assemble select histone modification enzymes, thereby specifying the pattern of histone modifications on target genes.

EGF decreases the abundance of microRNAs that restrain oncogenic transcription factors

Epidermal growth factor (EGF) stimulates cells by launching gene expression programs that are frequently deregulated in cancer. MicroRNAs, which attenuate gene expression by binding complementary regions in messenger RNAs, are broadly implicated in cancer. Using genome-wide approaches, we showed that EGF stimulation initiates a coordinated transcriptional program of microRNAs and transcription factors. The earliest event involved a decrease in the abundance of a subset of 23 microRNAs. This step permitted rapid induction of oncogenic transcription factors, such as c-FOS, encoded by immediate early genes. In line with roles as suppressors of EGF receptor (EGFR) signaling, we report that the abundance of this early subset of microRNAs is decreased in breast and in brain tumors driven by the EGFR or the closely related HER2. These findings identify specific microRNAs as attenuators of growth factor signaling and oncogenesis.

The effect of a handwashing intervention on preschool educator beliefs, attitudes, knowledge and self-efficacy

This paper describes the effect of a preschool hygiene intervention program on psychosocial measures of educators regarding handwashing and communicable pediatric disease. A cluster-randomized trial, with randomization at the level of the preschool, was run in 40 Jerusalem preschool classrooms. Eighty preschool educators participated. The program used a multipronged approach which included elements aimed at staff, children, parents, school nurses and the classroom environment. Frontal lectures by medical, epidemiological and educational experts, along with printed materials and experiential learning, were provided to staff. Responses from a validated survey instrument were used to build four scales for each respondent regarding beliefs, attitudes, self-efficacy and knowledge. The scales were built on a Likert-type 1-7 scale (1 = minimum, 7 = maximum). The effect of the intervention was tested using mixed model analysis of variance. Response was received from 92.5% of educators. Educators believed that handwashing could affect health (mean = 5.5, SD = 1.1), had high levels of self-efficacy (mean = 6.1, SD = 0.9) and had positive attitudes toward handwashing (mean = 5.7, SD = 1.2). Knowledge was affected by the intervention (intervention: mean = 6.2, SD = 0.7; control: mean = 5.8, SD = 0.8). The combination of positive attitudes toward handwashing among educators and the program's effectiveness in imparting knowledge helped to create a sustained social norm of handwashing among many children in disparate locations.

Co-occurrence of risk factors for cardiovascular disease by social class: 1958 British birth cohort

AIM

To establish whether social differences in multiple risk factors for cardiovascular disease are due to a greater strength of association (higher correlation) between risk factors in less advantaged groups.

METHODS

Co-occurrence of five risk factors (smoking, hypertension, low high-density lipoprotein cholesterol, obesity, diabetes) in 3614 British 45-year-old men and 3560 women in the manual and non-manual social groups.

RESULTS

4.0% of women in manual groups had >or=3 risk factors compared with 1.7% in non-manual groups: 6.2% and 3.4% respectively for men. There was a higher than expected percentage of the population, overall, with >or=3 risk factors assuming independence between risk factors; correspondingly, there was a slightly lower than expected proportion with one factor. However, patterns of observed to expected ratios were consistent in manual and non-manual groups and did not differ by the number of risk factors.

CONCLUSIONS

Higher prevalence of multiple risk factors in manual groups was due to the higher prevalence of individual factors rather than a greater tendency of those with an individual risk factor to have additional risks. Strategies to reduce multiple risk factors in less advantaged groups would help to lessen their health burden.

Examining cultural, psychosocial, community and behavioural factors in relationship to socioeconomic inequalities in limiting longstanding illness among the Arab minority in Israel

BACKGROUND

Few studies have examined the explanatory pathways to social inequalities in health within ethnic minorities. The current study examined the relative contributions of specific pathways explaining the associations between socioeconomic status (SES) and limiting longstanding illness (LLI) among the Arab minority in Israel.

METHODS

A cross-sectional study of a random sample of 902 individuals aged 30-70 selected in a multistage sampling procedure. SES was measured by education, land ownership and relative family income. Five-stage logistic regressions assessed the attenuations in the odds of LLI among those with lower SES compared to higher SES after including relevant groups of explanatory factors: psychosocial, behavioural and community, and their integration.

RESULTS

Rates of LLI were significantly higher in participants with lower SES. Inclusion of groups of explanatory variables attenuated all SES-LLI associations in a similar pattern: psychosocial factors played a main explanatory role, yielding 15-40% attenuation in odds ratios (OR). The contribution of community indicators was modest (10-21%); health behaviours had a marginal contribution (6-7%). Cultural factors were not associated with SES or LLI. The integrative model contributed up to 49% reduction in the OR.

CONCLUSIONS

The significant associations between SES and LLI suggest that formative policy to reduce SES-LLI disparities should emphasise creating opportunities for economic development to improve SES, which was the main predictor of inequalities. Combining strategies of community capacity building and reinforcement of individual inner resources might be complementary. Such conclusions might apply to other minorities in a similar context, for which future studies are required.

Cancer risk after exposure to treatments for ovulation induction

Uncertainty continues as to whether treatments for ovulation induction are associated with increased risk of cancer. The authors conducted a long-term population-based historical cohort study of parous women. A total of 15,030 women in the Jerusalem Perinatal Study who gave birth in 1974-1976 participated in a postpartum survey. Cancer incidence through 2004 was analyzed using Cox's proportional hazards models, controlling for age and other covariates. Women who used drugs to induce ovulation (n = 567) had increased risks of cancer at any site (multivariate hazard ratio (HR) = 1.36, 95% confidence interval (CI): 1.06, 1.74). An increased risk of uterine cancer was found among women treated with ovulation-inducing agents (HR = 3.39, 95% CI: 1.28, 8.97), specifically clomiphene (HR = 4.56, 95% CI: 1.56, 13.34). No association was noted between use of ovulation-inducing agents and ovarian cancer (age-adjusted HR = 0.61, 95% CI: 0.08, 4.42). Ovulation induction was associated with a borderline-significant increased risk of breast cancer (multivariate HR = 1.42, 95% CI: 0.99, 2.05). Increased risks were also observed for malignant melanoma and non-Hodgkin lymphoma. These associations appeared stronger among women who waited more than 1 year to conceive. Additional follow-up studies assessing these associations by drug type, dosage, and duration are needed.

Twin pregnancy and the risk of schizophrenia

BACKGROUND

Twins are exposed to intrauterine environments that differ significantly from those of singletons. These diverse environments might alter the risk for schizophrenia in twins and make it difficult to generalize from findings in twins when studying the risk of schizophrenia in the general population. Previous studies report contradictory findings on the risk for schizophrenia in twins.

METHODS

We studied the incidence of schizophrenia spectrum disorders, ascertained from Israel's National Psychiatric Registry, in a cohort of 2124 twins and 87,955 singletons. These offspring were followed from their birth in 1964-76 in the Jerusalem Perinatal study. Cox proportional hazards methods were used to compare outcomes over 28-41 years, adjusting for ages of parents.

RESULTS

Twins showed a relative risk [RR] of .84 relative to singletons, with a 95% confidence interval [CI] of (.51-1.4). RRs and CIs for males and females were .68 [.34-1.4] and 1.1 [.55-2.2] respectively. Twins in male-male, female-female or opposite-sex sets showed no significant variation in RRs; furthermore, first- or second-born twins did not differ significantly from each other. Siblings of twins had the same risk of schizophrenia as siblings of singletons.

CONCLUSION

Twins have the same risk for schizophrenia as the general population.