Genetic risk factors have a substantial impact on healthy life years

A scoping review of the assessment reports of genetic or genomic tests reveals inconsistent consideration of key dimensions of clinical utility

OBJECTIVES

Genetic and genomic tests are the cornerstone of personalized preventive approaches. Inconsistency in evaluating their clinical utility is often cited as a reason for their limited implementation in clinical practice. Previous reviews have primarily focused on theoretical frameworks used for clinical utility evaluations of genetic tests, rather than actual assessments and examined dimensions, rather than specific indicators within these dimensions. We aimed to review the dimensions and the specific indicators measured in published assessment reports of genetic or genomic tests.

STUDY DESIGN AND SETTING

We conducted a scoping review of assessment reports of genetic and genomic tests used for prevention, searching through PubMed, Web of Science, Scopus, the websites of 20 different organizations, Google, and Google Scholar. From the included assessments, we extracted the reported indicators of clinical utility, compiling a list of disease-specific indicators that detailed their numerator, denominator, and calculation methods. We analyzed the extracted indicators by stratifying them according to ten comprehensive dimensions of clinical utility, the assessment framework used, and the type of indicator (categorized as quantitative, qualitative, reference, or no evidence reported). From these indicators, we then distilled a list of general indicators.

RESULTS

We reviewed 3054 unique references and 12,000 results from gray literature searches, ultimately selecting 57 assessment reports. The reference frameworks used were health technology assessment (HTA) (42%), Evaluation of Genomic Applications in Practice and Prevention (EGAPP) (25%), ACCE (21%), and others (12%). We identified 951 disease-specific indicators. The dimensions most frequently evaluated (ie, had at least one indicator) were analytic validity (60%), clinical validity (79%), clinical efficacy (79%), and economic impact (58%). Only 12 assessments compared health outcomes between tested and untested groups, and fewer than 15% of the assessments addressed equity, acceptability, legitimacy, and personal value.

CONCLUSION

Our study illustrates that, although dimensions such as equity and acceptability, are significantly emphasized in traditional evaluation frameworks, these are often not considered in the assessments. Additionally, our study has underscored a significant dearth of reported primary evidence concerning the clinical efficacy of these tests.

PLAIN LANGUAGE SUMMARY

Genetic and genomic tests analyze a person's genes to predict health risks and guide healthcare decisions, potentially identifying who might benefit from certain treatments or check-ups. However, determining whether these tests are genuinely useful for wide use in health services is complex, because there is no standard way to define "clinical utility" of a genetic test. To understand how these tests are evaluated, we reviewed 57 evaluation reports from high-income countries, most of which focused on cancer-related genetic tests. We found that many evaluations looked mainly at how well a test predicted a condition (validity) and considered some form of effectiveness, yet often failed to measure whether the test truly improved patient health outcomes, such as lowering death rates or enhancing the quality of life. Moreover, factors like patient acceptance, equity, and personal relevance (eg, reducing anxiety) were frequently overlooked. Without including these broader considerations, evaluations risk missing critical evidence that would indicate whether a test is helpful, fair, and worth using. From over 900 unique indicators used to measure clinical utility, we created a simpler list of about 150 general indicators that can guide future evaluations. This consolidated list can help test developers decide which factors to investigate, evaluators determine what to measure, and policymakers identify what might be missing before deciding if a test should be adopted in healthcare. By highlighting the gaps-areas that should be assessed but currently are not-our study encourages a more comprehensive approach to evaluating genetic tests. If we fail to consider issues like equity, patient preferences, and proven health benefits, we risk investing in tests that may do little good or even harm patients. Ultimately, recognizing these shortcomings can lead to better-informed decisions, ensuring that genetic testing is used in ways that truly benefit patients and deliver safer, more personalized, and fairer healthcare for everyone.

Novel SLC16A2 Frameshift Mutation as a Cause of Allan-Herndon-Dudley Syndrome and its Implications for Carrier Screening

Background

Allan-Herndon-Dudley syndrome (AHDS) is a rare X-linked neurodevelopmental disorder caused by mutations in the solute carrier family 16-member 2 (SLC16A2) gene. This syndrome leads to significant psychomotor disabilities, thyroid dysfunction, and abnormal brain development. This case report describes the genetic cause of AHDS in a male proband and to expanding the mutation spectrum of the SLC16A2 gene.

Methods

A blood specimen was collected from a one-year-old child with delayed development and abnormal thyroid function and this was followed by whole-exome sequencing (WES) was performed on the proband to identify potential genetic mutations. Sanger sequencing was subsequently used to confirm the findings and determine the inheritance pattern of the mutation within the family.

Results

The proband, who presented with developmental delay, thyroid dysfunction, and abnormal brain development, was found to have a novel hemizygous frameshift mutation, c.513_538del (p.Ile172Cysfs*60), in the SLC16A2 gene (NM_006517.5). This mutation was inherited from his asymptomatic mother, confirming the X-linked inheritance pattern. The mutation is classified as likely pathogenic, contributing to the clinical presentation observed in the proband.

Conclusion

This study identified a novel frameshift mutation in the SLC16A2 gene associated with AHDS, thereby expanding the known mutation spectrum of this gene. Given the significant impact of AHDS on neural development and hormone secretion, it is recommended that this gene be included in carrier screening panels in China, particularly for families with a history of related neurodevelopmental disorders.

Polygenic Risk Scores in Human Disease

BACKGROUND

Polygenic risk scores (PRS) are measures of genetic susceptibility to human health traits. With the advent of large data repositories combining genetic data and phenotypic information, PRS are providing valuable insights into the genetic architecture of complex diseases and are transforming the landscape of precision medicine.

CONTENT

PRS have emerged as tools with clinical utility in human disease. Herein, details on how to develop PRS are provided, followed by 5 areas in which they can be used to improve human health: (a) augmenting risk prediction, (b) refining diagnosis, (c) guiding treatment choices, (d) making clinical trials more efficient, and (e) improving public health. Finally, some of the ongoing challenges to the clinical implementation of PRS are noted.

SUMMARY

PRS can offer valuable information for providers and patients, including identifying risk of disease earlier in life and before the onset of clinical risk factors, guiding treatment decisions, improving public health outcomes, and making clinical trials more efficient. The future of genomic-informed risk assessments of disease is through integrated risk models that combine genetic factors including PRS, monogenic, and somatic DNA information with nongenetic risk factors such as clinical risk estimators and multiomic data. However, adopting PRS in a clinical setting at scale faces some challenges, including cross-ancestry performance, standardization and calibration of risk models, downstream clinical decision-making from risk information, and seamless integration into existing health systems.

Demographic diversity in platelet function and response to antiplatelet therapy

Recent studies have highlighted the complexity of platelet biology, revealing their diverse roles beyond hemostasis. Pathological platelet activation is now recognized as a key contributor to thrombosis and inflammation that are both central to cardiovascular disease (CVD). Emerging research emphasizes the significant impact of demographic factors - such as age, sex, race, and ethnicity - on CVD risk and responses to antiplatelet therapies. These population-based differences, shaped by genetic and non-genetic factors, highlight the need for reevaluation of antiplatelet strategies. We address current knowledge and emphasize the pressing need for further research into platelet biology and cardiovascular outcomes across diverse populations. In this review we advocate for tailored therapeutic approaches in CVD based on the recent demographic-focused findings.

Screening embryos for polygenic disease risk: a review of epidemiological, clinical, and ethical considerations

BACKGROUND

The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural variants, and aneuploidy. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, raising the possibility of screening embryos for their risk of polygenic diseases such as breast cancer, hypertension, diabetes, or schizophrenia. Despite a heated debate around this new technology, called polygenic embryo screening (PES; also PGT-P), it is already available to IVF patients in some countries. Several articles have studied epidemiological, clinical, and ethical perspectives on PES; however, a comprehensive, principled review of this emerging field is missing.

OBJECTIVE AND RATIONALE

This review has four main goals. First, given the interdisciplinary nature of PES studies, we aim to provide a self-contained educational background about PES to reproductive specialists interested in the subject. Second, we provide a comprehensive and critical review of arguments for and against the introduction of PES, crystallizing and prioritizing the key issues. We also cover the attitudes of IVF patients, clinicians, and the public towards PES. Third, we distinguish between possible future groups of PES patients, highlighting the benefits and harms pertaining to each group. Finally, our review, which is supported by ESHRE, is intended to aid healthcare professionals and policymakers in decision-making regarding whether to introduce PES in the clinic, and if so, how, and to whom.

SEARCH METHODS

We searched for PubMed-indexed articles published between 1/1/2003 and 1/3/2024 using the terms 'polygenic embryo screening', 'polygenic preimplantation', and 'PGT-P'. We limited the review to primary research papers in English whose main focus was PES for medical conditions. We also included papers that did not appear in the search but were deemed relevant.

OUTCOMES

The main theoretical benefit of PES is a reduction in lifetime polygenic disease risk for children born after screening. The magnitude of the risk reduction has been predicted based on statistical modelling, simulations, and sibling pair analyses. Results based on all methods suggest that under the best-case scenario, large relative risk reductions are possible for one or more diseases. However, as these models abstract several practical limitations, the realized benefits may be smaller, particularly due to a limited number of embryos and unclear future accuracy of the risk estimates. PES may negatively impact patients and their future children, as well as society. The main personal harms are an unindicated IVF treatment, a possible reduction in IVF success rates, and patient confusion, incomplete counselling, and choice overload. The main possible societal harms include discarded embryos, an increasing demand for 'designer babies', overemphasis of the genetic determinants of disease, unequal access, and lower utility in people of non-European ancestries. Benefits and harms will vary across the main potential patient groups, comprising patients already requiring IVF, fertile people with a history of a severe polygenic disease, and fertile healthy people. In the United States, the attitudes of IVF patients and the public towards PES seem positive, while healthcare professionals are cautious, sceptical about clinical utility, and concerned about patient counselling.

WIDER IMPLICATIONS

The theoretical potential of PES to reduce risk across multiple polygenic diseases requires further research into its benefits and harms. Given the large number of practical limitations and possible harms, particularly unnecessary IVF treatments and discarded viable embryos, PES should be offered only within a research context before further clarity is achieved regarding its balance of benefits and harms. The gap in attitudes between healthcare professionals and the public needs to be narrowed by expanding public and patient education and providing resources for informative and unbiased genetic counselling.

The China Kadoorie Biobank Collaborative Group, Sun D, Ding Y, Yu C, Sun D, Pang Y, Pei P, Yang L, Millwood IY, Walters RG, Du H, Chen X, Schmidt D, Stevens R, Chen J, Chen Z, Li L, Lv J. Joint impact of polygenic risk score and lifestyles on early- and late-onset cardiovascular diseases

Understanding the interactions between genetic risk and lifestyles on different types and age onsets of cardiovascular disease (CVD) risk can help identify individuals for whom lifestyle changes would be beneficial. Here we developed three polygenic risk scores, called MetaPRSs, for coronary artery disease, ischaemic stroke and intracerebral haemorrhage by combining PRSs for CVD and CVD-related risk factors in 96,400 participants from the prospective China Kadoorie Biobank. Genetic and lifestyle risks were categorized by the disease-specific MetaPRSs and the number of unfavourable lifestyles. High genetic risk and unfavourable lifestyles were found to be more strongly associated with early than late onset of CVD outcomes in men and women. Change from unfavourable to favourable lifestyles resulted in 14.7-, 2.5- and 2.6-fold greater reductions in incidence rates of early-onset coronary artery disease and ischaemic stroke and late-onset coronary artery disease in high than low genetic risk group. Young adults at high genetic risk may have larger benefits in preventing CVD from lifestyle improvements.

Polygenic prediction of human longevity on the supposition of pervasive pleiotropy

The highly polygenic nature of human longevity renders pleiotropy an indispensable feature of its genetic architecture. Leveraging the genetic correlation between aging-related traits (ARTs), we aimed to model the additive variance in lifespan as a function of the cumulative liability from pleiotropic segregating variants. We tracked allele frequency changes as a function of viability across different age bins and prioritized 34 variants with an immediate implication on lipid metabolism, body mass index (BMI), and cognitive performance, among other traits, revealed by PheWAS analysis in the UK Biobank. Given the highly complex and non-linear interactions between the genetic determinants of longevity, we reasoned that a composite polygenic score would approximate a substantial portion of the variance in lifespan and developed the integrated longevity genetic scores (iLGSs) for distinguishing exceptional survival. We showed that coefficients derived from our ensemble model could potentially reveal an interesting pattern of genomic pleiotropy specific to lifespan. We assessed the predictive performance of our model for distinguishing the enrichment of exceptional longevity among long-lived individuals in two replication cohorts (the Scripps Wellderly cohort and the Medical Genome Reference Bank (MRGB)) and showed that the median lifespan in the highest decile of our composite prognostic index is up to 4.8 years longer. Finally, using the proteomic correlates of iLGS, we identified protein markers associated with exceptional longevity irrespective of chronological age and prioritized drugs with repurposing potentials for gerotherapeutics. Together, our approach demonstrates a promising framework for polygenic modeling of additive liability conferred by ARTs in defining exceptional longevity and assisting the identification of individuals at a higher risk of mortality for targeted lifestyle modifications earlier in life. Furthermore, the proteomic signature associated with iLGS highlights the functional pathway upstream of the PI3K-Akt that can be effectively targeted to slow down aging and extend lifespan.

The relationship between 11 different polygenic longevity scores, parental lifespan, and disease diagnosis in the UK Biobank

Large-scale genome-wide association studies (GWAS) strongly suggest that most traits and diseases have a polygenic component. This observation has motivated the development of disease-specific "polygenic scores (PGS)" that are weighted sums of the effects of disease-associated variants identified from GWAS that correlate with an individual's likelihood of expressing a specific phenotype. Although most GWAS have been pursued on disease traits, leading to the creation of refined "Polygenic Risk Scores" (PRS) that quantify risk to diseases, many GWAS have also been pursued on extreme human longevity, general fitness, health span, and other health-positive traits. These GWAS have discovered many genetic variants seemingly protective from disease and are often different from disease-associated variants (i.e., they are not just alternative alleles at disease-associated loci) and suggest that many health-positive traits also have a polygenic basis. This observation has led to an interest in "polygenic longevity scores (PLS)" that quantify the "risk" or genetic predisposition of an individual towards health. We derived 11 different PLS from 4 different available GWAS on lifespan and then investigated the properties of these PLS using data from the UK Biobank (UKB). Tests of association between the PLS and population structure, parental lifespan, and several cancerous and non-cancerous diseases, including death from COVID-19, were performed. Based on the results of our analyses, we argue that PLS are made up of variants not only robustly associated with parental lifespan, but that also contribute to the genetic architecture of disease susceptibility, morbidity, and mortality.

A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk

Polygenic scores (PGSs) offer the ability to predict genetic risk for complex diseases across the life course; a key benefit over short-term prediction models. To produce risk estimates relevant to clinical and public health decision-making, it is important to account for varying effects due to age and sex. Here, we develop a novel framework to estimate country-, age-, and sex-specific estimates of cumulative incidence stratified by PGS for 18 high-burden diseases. We integrate PGS associations from seven studies in four countries (N = 1,197,129) with disease incidences from the Global Burden of Disease. PGS has a significant sex-specific effect for asthma, hip osteoarthritis, gout, coronary heart disease and type 2 diabetes (T2D), with all but T2D exhibiting a larger effect in men. PGS has a larger effect in younger individuals for 13 diseases, with effects decreasing linearly with age. We show for breast cancer that, relative to individuals in the bottom 20% of polygenic risk, the top 5% attain an absolute risk for screening eligibility 16.3 years earlier. Our framework increases the generalizability of results from biobank studies and the accuracy of absolute risk estimates by appropriately accounting for age- and sex-specific PGS effects. Our results highlight the potential of PGS as a screening tool which may assist in the early prevention of common diseases.

Severity of effect considerations regarding the use of mutation as a toxicological endpoint for risk assessment: A report from the 8th International Workshop on Genotoxicity Testing (IWGT)

Exposure levels without appreciable human health risk may be determined by dividing a point of departure on a dose-response curve (e.g., benchmark dose) by a composite adjustment factor (AF). An "effect severity" AF (ESAF) is employed in some regulatory contexts. An ESAF of 10 may be incorporated in the derivation of a health-based guidance value (HBGV) when a "severe" toxicological endpoint, such as teratogenicity, irreversible reproductive effects, neurotoxicity, or cancer was observed in the reference study. Although mutation data have been used historically for hazard identification, this endpoint is suitable for quantitative dose-response modeling and risk assessment. As part of the 8th International Workshops on Genotoxicity Testing, a sub-group of the Quantitative Analysis Work Group (WG) explored how the concept of effect severity could be applied to mutation. To approach this question, the WG reviewed the prevailing regulatory guidance on how an ESAF is incorporated into risk assessments, evaluated current knowledge of associations between germline or somatic mutation and severe disease risk, and mined available data on the fraction of human germline mutations expected to cause severe disease. Based on this review and given that mutations are irreversible and some cause severe human disease, in regulatory settings where an ESAF is used, a majority of the WG recommends applying an ESAF value between 2 and 10 when deriving a HBGV from mutation data. This recommendation may need to be revisited in the future if direct measurement of disease-causing mutations by error-corrected next generation sequencing clarifies selection of ESAF values.

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990-2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND

Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021.

METHODS

The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk-outcome pairs. Pairs were included on the basis of data-driven determination of a risk-outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk-outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk-outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws.

FINDINGS

Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7-9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4-9·2]), smoking (5·7% [4·7-6·8]), low birthweight and short gestation (5·6% [4·8-6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8-6·0]). For younger demographics (ie, those aged 0-4 years and 5-14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9-27·7]) and environmental and occupational risks (decrease of 22·0% [15·5-28·8]), coupled with a 49·4% (42·3-56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9-21·7] for high BMI and 7·9% [3·3-12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6-1·9) for high BMI and 1·3% (1·1-1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4-78·8) for child growth failure and 66·3% (60·2-72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP).

INTERPRETATION

Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions.

FUNDING

Bill & Melinda Gates Foundation.

Genetic modifiers of rare variants in monogenic developmental disorder loci

Rare damaging variants in a large number of genes are known to cause monogenic developmental disorders (DDs) and have also been shown to cause milder subclinical phenotypes in population cohorts. Here, we show that carrying multiple (2-5) rare damaging variants across 599 dominant DD genes has an additive adverse effect on numerous cognitive and socioeconomic traits in UK Biobank, which can be partially counterbalanced by a higher educational attainment polygenic score (EA-PGS). Phenotypic deviators from expected EA-PGS could be partly explained by the enrichment or depletion of rare DD variants. Among carriers of rare DD variants, those with a DD-related clinical diagnosis had a substantially lower EA-PGS and more severe phenotype than those without a clinical diagnosis. Our results suggest that the overall burden of both rare and common variants can modify the expressivity of a phenotype, which may then influence whether an individual reaches the threshold for clinical disease.

Impact of SGLT-2 inhibitors on modifiable cardiovascular risk factors in Romanian patients with type 2 diabetes mellitus

BACKGROUND

Modifiable cardiovascular risk factors are high blood pressure, smoking, diabetes, sedentary lifestyle, obesity, and hypercholesterolemia.

AIM

To investigate the impact of sodium-glucose 2 co-transporter inhibitors (SGLT-2i) on modifiable cardiovascular risk factors in Romanian patients diagnosed with type 2 diabetes mellitus (T2DM).

METHOD

A retrospective study was conducted on 200 Romanian patients with T2DM who were being treated with SGLT-2i, either Dapagliflozin or Empagliflozin. Collected data included demographic characteristics, such as weight, body mass index (BMI), fasting blood glucose (FBG), creatinine, glycated hemoglobin (HbA1c), abdominal circumference (AC), urine albumin-to-creatinine ratio (UACR), systolic blood pressure (SBP), diastolic blood pressure (DBP), C-reactive protein (CRP) and N-terminal pro b-type natriuretic peptide (NT-proBNP). The patients were observed for one year after being treated with SGLT-2i.

RESULTS

The mean value of FBG decreased from 180.00 mg% (IQR: 154.50-207.00) to 130.00 mg% (IQR: 117.50-150.00) (p < 0.001), and the mean of HbA1c values decreased from 8.40% (IQR: 7.98-9.15%) to 7.30% (IQR: 6.90-7.95%) (p < 0.001). We also obtained significant positive effects on body weight, i.e., the weight decreased from 90.50 kg (82.00-106.50) to 89.00 kg (77.50-100.00) (p = 0.018), BMI from 32.87 kg/m2 (29.24-36.45) to 31.00 kg/m2 (27.74-34.71) (p < 0.001) and AC from 107.05 (± 16.39) to 102.50 (± 15.11) (p = 0.042). The UACR decreased from 23.98 mg/g (19.76-36.85) to 19.39 mg/g (1.30-24.29) (p < 0.001). Initially, the median value for SBP was 140.00mmgHg (130.00-160.00), and for DBP was 80.00 mmgHg (72.00-90.00), and one year after treatment, the medium value was 120.00 mmgHg (115.50-130.00) for SBP (p < 0.001), and 72.00 mmgHg (70.00-78.00) for DBP (p < 0.001) The mean CRP values decreased from 68.00 mg/dL (56.25-80.25) to 34.00 mg/dL (28.12-40.12) (p < 0.001), and the mean NT-proBNP decreased from 146.00pg/mL (122.50-170.50) to 136.00 pg/mL (112.50-160.50) (p = 0.005).

CONCLUSION

Treatment with SGLT-2i in Romanian patients with T2DM has beneficial effects on modifiable cardiovascular risk factors.

The Health History of First-Degree Relatives' Dyslipidemia Can Affect Preferences and Intentions following the Return of Genomic Results for Monogenic Familial Hypercholesterolemia

Genetic testing is key in modern healthcare, particularly for monogenic disorders such as familial hypercholesterolemia. This Tohoku Medical Megabank Project study explored the impact of first-degree relatives' dyslipidemia history on individual responses to familial hypercholesterolemia genomic results. Involving 214 participants and using Japan's 3.5KJPN genome reference panel, the study assessed preferences and intentions regarding familial hypercholesterolemia genetic testing results. The data revealed a significant inclination among participants with a family history of dyslipidemia to share their genetic test results, with more than 80% of participants intending to share positive results with their partners and children and 98.1% acknowledging the usefulness of positive results for personal health management. The study underscores the importance of family health history in genetic-testing perceptions, highlighting the need for family-centered approaches in genetic counseling and healthcare. Notable study limitations include the regional scope and reliance on questionnaire data. The study results emphasize the association between family health history and genetic-testing attitudes and decisions.

An immunogenetic basis for lung cancer risk

Cancer risk is influenced by inherited mutations, DNA replication errors, and environmental factors. However, the influence of genetic variation in immunosurveillance on cancer risk is not well understood. Leveraging population-level data from the UK Biobank and FinnGen, we show that heterozygosity at the human leukocyte antigen (HLA)-II loci is associated with reduced lung cancer risk in smokers. Fine-mapping implicated amino acid heterozygosity in the HLA-II peptide binding groove in reduced lung cancer risk, and single-cell analyses showed that smoking drives enrichment of proinflammatory lung macrophages and HLA-II+ epithelial cells. In lung cancer, widespread loss of HLA-II heterozygosity (LOH) favored loss of alleles with larger neopeptide repertoires. Thus, our findings nominate genetic variation in immunosurveillance as a critical risk factor for lung cancer.

A deep learning transformer model predicts high rates of undiagnosed rare disease in large electronic health systems

It is estimated that as many as 1 in 16 people worldwide suffer from rare diseases. Rare disease patients face difficulty finding diagnosis and treatment for their conditions, including long diagnostic odysseys, multiple incorrect diagnoses, and unavailable or prohibitively expensive treatments. As a result, it is likely that large electronic health record (EHR) systems include high numbers of participants suffering from undiagnosed rare disease. While this has been shown in detail for specific diseases, these studies are expensive and time consuming and have only been feasible to perform for a handful of the thousands of known rare diseases. The bulk of these undiagnosed cases are effectively hidden, with no straightforward way to differentiate them from healthy controls. The ability to access them at scale would enormously expand our capacity to study and develop drugs for rare diseases, adding to tools aimed at increasing availability of study cohorts for rare disease. In this study, we train a deep learning transformer algorithm, RarePT (Rare-Phenotype Prediction Transformer), to impute undiagnosed rare disease from EHR diagnosis codes in 436,407 participants in the UK Biobank and validated on an independent cohort from 3,333,560 individuals from the Mount Sinai Health System. We applied our model to 155 rare diagnosis codes with fewer than 250 cases each in the UK Biobank and predicted participants with elevated risk for each diagnosis, with the number of participants predicted to be at risk ranging from 85 to 22,000 for different diagnoses. These risk predictions are significantly associated with increased mortality for 65% of diagnoses, with disease burden expressed as disability-adjusted life years (DALY) for 73% of diagnoses, and with 72% of available disease-specific diagnostic tests. They are also highly enriched for known rare diagnoses in patients not included in the training set, with an odds ratio (OR) of 48.0 in cross-validation cohorts of the UK Biobank and an OR of 30.6 in the independent Mount Sinai Health System cohort. Most importantly, RarePT successfully screens for undiagnosed patients in 32 rare diseases with available diagnostic tests in the UK Biobank. Using the trained model to estimate the prevalence of undiagnosed disease in the UK Biobank for these 32 rare phenotypes, we find that at least 50% of patients remain undiagnosed for 20 of 32 diseases. These estimates provide empirical evidence of a high prevalence of undiagnosed rare disease, as well as demonstrating the enormous potential benefit of using RarePT to screen for undiagnosed rare disease patients in large electronic health systems.

Association of APOE Haplotypes With Common Age-Related Ocular Diseases in 412,171 Individuals

Purpose

Apolipoprotein E4 (APOE4), a known risk factor for Alzheimer's disease, has controversially been associated with reduced risk of primary open-angle glaucoma (POAG) and age-related macular degeneration (AMD). Here, we sought to systematically quantify the associations of APOE haplotypes with age-related ocular diseases and to assess their scope and age-dependency.

Methods

We included genetic and registry data from 412,171 Finnish individuals in the FinnGen study. Disease endpoints were defined using nationwide registries. APOE genotypes were directly genotyped using Illumina and Affymetrix arrays or imputed using a custom Finnish reference panel. We evaluated the disease associations of APOE genotypes containing ε2 (without ε4) and ε4 (without ε2) compared with the ε3ε3 genotype using logistic regressions stratified by age.

Results

APOE ε4 enriched haplotypes were inversely associated with overall glaucoma (odds ratio [OR] = 0.95, 95% confidence interval [CI] = 0.92-0.99, P = 0.0047), and its subtypes POAG (OR = 0.95, P = 0.027), normal-tension glaucoma (OR = 0.87, P = 0.0058), and suspected glaucoma (OR = 0.95, P = 0.014). Individuals with the ε4 allele also had lower odds for AMD (OR = 0.80, 95% CI = 0.76-0.84, P < 0.001), seen both in dry and neovascular subgroups. A slight negative association was also detected in senile cataract, but this was not reproducible in age-group analyses.

Conclusions

Our results support prior evidence of the inverse association of APOE ε4 with glaucoma, but the association was weaker than for AMD. We could not show an association with exfoliation glaucoma, supporting the hypothesis that APOE may be involved in regulating retinal ganglion cell degeneration rather than intraocular pressure.

Frequency of actionable secondary findings in 7472 Korean genomes derived from the National Project of Bio Big Data pilot study

Exome and genome sequencing (ES/GS) in genetic medicine and research leads to discovering genomic secondary findings (SFs) unrelated to the purpose of the primary test. There is a lack of agreement to return the SF results for individuals undergoing the test. The aim of this study is to investigate the frequency of actionable secondary findings using GS data obtained from the rare disease study and the Korean Genome and Epidemiology Study (KoGES) in the National Project of Bio Big Data pilot study. Pathogenic (P) or likely pathogenic (LP) variants of 78 SF genes recommended by the American College of Medical Genetics and Genomics (ACMG) were screened in the rare disease study and KoGES. The pathogenicity of SF gene variants was determined according to the ACMG interpretation. The overall SF rate was 3.75% for 280 individuals with 298 P/LP variants of 41 ACMG SF genes which were identified among 7472 study participants. The frequencies of genes associated with cardiovascular, cancer, and miscellaneous phenotypes were 2.17%, 1.22%, and 0.58%, respectively. The most frequent SF gene was TTN followed by BRCA2. The frequency of actionable SFs among participants with rare disease and general population participants in the Korean population presented here will assist in reporting results of medically actionable SFs in genomic medicine.

Associations of polygenic inheritance of physical activity with aerobic fitness, cardiometabolic risk factors and diseases: the HUNT study

Physical activity (PA), aerobic fitness, and cardiometabolic diseases (CMD) are highly heritable multifactorial phenotypes. Shared genetic factors may underlie the associations between higher levels of PA and better aerobic fitness and a lower risk for CMDs. We aimed to study how PA genotype associates with self-reported PA, aerobic fitness, cardiometabolic risk factors and diseases. PA genotype, which combined variation in over one million of gene variants, was composed using the SBayesR polygenic scoring methodology. First, we constructed a polygenic risk score for PA in the Trøndelag Health Study (N = 47,148) using UK Biobank single nucleotide polymorphism-specific weights (N = 400,124). The associations of the PA PRS and continuous variables were analysed using linear regression models and with CMD incidences using Cox proportional hazard models. The results showed that genotypes predisposing to higher amount of PA were associated with greater self-reported PA (Beta [B] = 0.282 MET-h/wk per SD of PRS for PA, 95% confidence interval [CI] = 0.211, 0.354) but not with aerobic fitness. These genotypes were also associated with healthier cardiometabolic profile (waist circumference [B = -0.003 cm, 95% CI = -0.004, -0.002], body mass index [B = -0.002 kg/m2, 95% CI = -0.004, -0.001], high-density lipoprotein cholesterol [B = 0.004 mmol/L, 95% CI = 0.002, 0.006]) and lower incidence of hypertensive diseases (Hazard Ratio [HR] = 0.97, 95% CI = 0.951, 0.990), stroke (HR = 0.94, 95% CI = 0.903, 0.978) and type 2 diabetes (HR = 0.94, 95 % CI = 0.902, 0.970). Observed associations were independent of self-reported PA. These results support earlier findings suggesting small pleiotropic effects between PA and CMDs and provide new evidence about associations of polygenic inheritance of PA and intermediate cardiometabolic risk factors.

Primary care providers' preferences for the communication and management of actionable genomic findings from a research biobank

Purpose

Little is known about non-genetics health care specialists' attitudes toward the return and utilization of actionable genomic results from a research biobank. We surveyed primary care providers (PCPs) to explore their perspectives on these results and their preferences for return.

Methods

We administered a paper and web-based 27-question survey to PCPs residing locally and caring for adult patients. Recruitment was conducted in person and by email, focusing on PCPs likely to interact with results generated by our institution's biobank.

Results

Of the ~482 PCPs contacted, 77 (16%) returned surveys. Although most respondents (90%) prefer that a genetics specialist be involved in communicating biobank-generated genomic results to patients, about 40% of respondents reported that a PCP shares the responsibility to discuss these results along with other specialists. A majority of respondents (74%) felt uncomfortable communicating these results to patients. However, respondents reported significantly greater comfort with this process when offered targeted educational resources (62% with vs 10% without resources; P < 10-5).

Conclusion

PCPs recognize the need to engage with their patients' biobank-generated genomic results but feel uncomfortable in doing so. Relevant resources are needed to improve PCPs' confidence in the use of these types of results to affect patient care.

A FinnGen pilot clinical recall study for Alzheimer's disease

Successful development of novel therapies requires that clinical trials are conducted in patient cohorts with the highest benefit-to-risk ratio. Population-based biobanks with comprehensive health and genetic data from large numbers of individuals hold promise to facilitate identification of trial participants, particularly when interventions need to start while symptoms are still mild, such as for Alzheimer's disease (AD). This study describes a process for clinical recall studies from FinnGen. We demonstrate the feasibility to systematically ascertain customized clinical data from FinnGen participants with ICD10 diagnosis of AD or mild cognitive disorder (MCD) in a single-center cross-sectional study testing blood-based biomarkers and cognitive functioning in-person, computer-based and remote. As a result, 19% (27/140) of a pre-specified FinnGen subcohort were successfully recalled and completed the study. Hospital records largely validated registry entries. For 8/12 MCD patients, other reasons than AD were identified as underlying diagnosis. Cognitive measures correlated across platforms, with highest consistencies for dementia screening (r = 0.818) and semantic fluency (r = 0.764), respectively, for in-person versus telephone-administered tests. Glial fibrillary acidic protein (GFAP) (p < 0.002) and phosphorylated-tau 181 (pTau-181) (p < 0.020) most reliably differentiated AD from MCD participants. We conclude that informative, customized clinical recall studies from FinnGen are feasible.

Inflammation compared to low-density lipoprotein cholesterol: two different causes of atherosclerotic cardiovascular disease

PURPOSE OF REVIEW

Inflammation is gaining attention as a target for prevention of atherosclerotic cardiovascular disease (ASCVD). The purpose of this review is to compare the evidence for inflammation with the evidence for low-density lipoprotein (LDL) cholesterol in ASCVD.

RECENT FINDINGS

Evidence from human genetic studies and randomized controlled trials implicate the inflammatory pathway from the inflammasome through interleukin (IL)-1 to IL-6 as a cause of ASCVD. Higher levels of IL-6 may lead to proportionally increased risk of ASCVD, and randomized controlled trials of IL-6 inhibitors are underway. The causal evidence for LDL cholesterol in ASCVD is overwhelming and recent important findings instead revolve around development of improved LDL cholesterol lowering therapy through RNA and DNA based therapeutics. Even though some lipid-lowering therapies lower IL-6, the IL-6 inflammatory pathway and LDL cholesterol are two separate causes of ASCVD.

SUMMARY

IL-6 mediated inflammation most likely causes ASCVD, in parallel with LDL cholesterol. However, fewer individuals in the general population are exposed to high IL-6 than high LDL cholesterol. For inflammation, future research should focus on improving efficacy and safety of anti-inflammatory therapy, and for LDL cholesterol, future research should focus on wider and more effective implementation of LDL cholesterol lowering therapy.

Genetic and epigenetic background of diabetic kidney disease

Diabetic kidney disease (DKD) is a severe diabetic complication that affects up to half of the individuals with diabetes. Elevated blood glucose levels are a key underlying cause of DKD, but DKD is a complex multifactorial disease, which takes years to develop. Family studies have shown that inherited factors also contribute to the risk of the disease. During the last decade, genome-wide association studies (GWASs) have emerged as a powerful tool to identify genetic risk factors for DKD. In recent years, the GWASs have acquired larger number of participants, leading to increased statistical power to detect more genetic risk factors. In addition, whole-exome and whole-genome sequencing studies are emerging, aiming to identify rare genetic risk factors for DKD, as well as epigenome-wide association studies, investigating DNA methylation in relation to DKD. This article aims to review the identified genetic and epigenetic risk factors for DKD.

Nutrigenomics in the context of evolution

Nutrigenomics describes the interaction between nutrients and our genome. Since the origin of our species most of these nutrient-gene communication pathways have not changed. However, our genome experienced over the past 50,000 years a number of evolutionary pressures, which are based on the migration to new environments concerning geography and climate, the transition from hunter-gatherers to farmers including the zoonotic transfer of many pathogenic microbes and the rather recent change of societies to a preferentially sedentary lifestyle and the dominance of Western diet. Human populations responded to these challenges not only by specific anthropometric adaptations, such as skin color and body stature, but also through diversity in dietary intake and different resistance to complex diseases like the metabolic syndrome, cancer and immune disorders. The genetic basis of this adaptation process has been investigated by whole genome genotyping and sequencing including that of DNA extracted from ancient bones. In addition to genomic changes, also the programming of epigenomes in pre- and postnatal phases of life has an important contribution to the response to environmental changes. Thus, insight into the variation of our (epi)genome in the context of our individual's risk for developing complex diseases, helps to understand the evolutionary basis how and why we become ill. This review will discuss the relation of diet, modern environment and our (epi)genome including aspects of redox biology. This has numerous implications for the interpretation of the risks for disease and their prevention.

A Shared Genetic Signature for Common Chronic Pain Conditions and its Impact on Biopsychosocial Traits

The multiple comorbidities & dimensions of chronic pain present a formidable challenge in disentangling its aetiology. Here, we performed genome-wide association studies of 8 chronic pain types using UK Biobank data (N =4,037-79,089 cases; N = 239,125 controls), followed by bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine (respectively) their genetic correlations and genetic causal proportion (GCP) parameters with 1,492 other complex traits. We report evidence of a shared genetic signature across chronic pain types as their genetic correlations and GCP directions were broadly consistent across an array of biopsychosocial traits. Across 5,942 significant genetic correlations, 570 trait pairs could be explained by a causal association (|GCP| >0.6; 5% false discovery rate), including 82 traits affected by pain while 410 contributed to an increased risk of chronic pain (cf. 78 with a decreased risk) such as certain somatic pathologies (eg, musculoskeletal), psychiatric traits (eg, depression), socioeconomic factors (eg, occupation) and medical comorbidities (eg, cardiovascular disease). This data-driven phenome-wide association analysis has demonstrated a novel and efficient strategy for identifying genetically supported risk & protective traits to enhance the design of interventional trials targeting underlying causal factors and accelerate the development of more effective treatments with broader clinical utility. PERSPECTIVE: Through large-scale phenome-wide association analyses of >1,400 biopsychosocial traits, this article provides evidence for a shared genetic signature across 8 common chronic pain types. It lays the foundation for further translational studies focused on identifying causal genetic variants and pathophysiological pathways to develop novel diagnostic & therapeutic technologies and strategies.

Portability of Polygenic Risk Scores for Sleep Duration, Insomnia and Chronotype in 33,493 Individuals

Polygenic risk scores (PRSs) estimate genetic liability for diseases and traits. However, the portability of PRSs in sleep traits has remained elusive. We generated PRSs for self-reported insomnia, chronotype and sleep duration using summary data from genome-wide association studies (GWASs) performed in 350,000 to 697,000 European-ancestry individuals. We then projected the scores in two independent Finnish population cohorts (N = 33,493) and tested whether the PRSs were associated with their respective sleep traits. We observed that all the generated PRSs were associated with their corresponding traits (p < 0.05 in all cases). Furthermore, we found that there was a 22.2 min difference in reported sleep between the 5% tails of the PRS for sleep duration (p < 0.001). Our findings indicate that sleep-related PRSs show portability across cohorts. The findings also demonstrate that sleep measures using PRSs for sleep behaviors may provide useful instruments for testing disease and trait associations in cohorts where direct sleep parameters have not yet been measured.

Translational opportunities emerge from genetic influences on health

Jukarainen et al. provide a novel perspective on the interpretation of heritable risk factors and human health. This study provides opportunities to focus translational efforts, characterize genetic influences on disease disparities, and improve communication between clinicians and patients regarding genetic risks. We describe their approach and discuss its implications, utility, and limitations.