Fine-scale population structure and demographic history of British Pakistanis

Modeling the effects of consanguinity on autosomal and X-chromosomal runs of homozygosity and identity-by-descent sharing

Runs of homozygosity (ROH) and identity-by-descent (IBD) sharing can be studied in diploid coalescent models by noting that ROH and IBD-sharing at a genomic site are predicted to be inversely related to coalescence times-which in turn can be mathematically obtained in terms of parameters describing consanguinity rates. Comparing autosomal and X-chromosomal coalescent models, we consider ROH and IBD-sharing in relation to consanguinity that proceeds via multiple forms of first-cousin mating. We predict that across populations with different levels of consanguinity, (1) in a manner that is qualitatively parallel to the increase of autosomal IBD-sharing with autosomal ROH, X-chromosomal IBD-sharing increases with X-chromosomal ROH, owing to the dependence of both quantities on consanguinity levels; (2) even in the absence of consanguinity, X-chromosomal ROH and IBD-sharing levels exceed corresponding values for the autosomes, owing to the smaller population size and lower coalescence time for the X chromosome than for autosomes; (3) with matrilateral consanguinity, the relative increase in ROH and IBD-sharing on the X chromosome compared to the autosomes is greater than in the absence of consanguinity. Examining genome-wide SNPs in human populations for which consanguinity levels have been estimated, we find that autosomal and X-chromosomal ROH and IBD-sharing levels generally accord with the predictions. We find that each 1% increase in autosomal ROH is associated with an increase of 2.1% in X-chromosomal ROH, and each 1% increase in autosomal IBD-sharing is associated with an increase of 1.6% in X-chromosomal IBD-sharing. For each calculation, particularly for ROH, the estimate is reasonably close to the increase of 2% predicted by the population-size difference between autosomes and X chromosomes. The results support the utility of coalescent models for understanding patterns of genomic sharing and their dependence on sex-biased processes.

South Asia: The Missing Diverse in Diversity

South Asia, making up around 25% of the world's population, encompasses a wide range of individuals with tremendous genetic and environmental diversity. This region, which spans eight countries, is home to over 4500 anthropologically defined groups that speak numerous languages and have an array of religious beliefs and cultures, making it one of the most diverse places in the world. Much of the region's rich genetic diversity and structure is the result of a complex combination of population history, migration patterns, and endogamous practices. Despite the overwhelming size and diversity, South Asians have often been underrepresented in genetic research, making up less than 2% of the participants in genetic studies. This has led to a lack of population specific understanding of genetic disease risks. We aim to raise awareness about underlying genetic diversity in this ancestry group, call attention to the lack of representation of the group, and to highlight strategies for future studies in South Asians.

Influence of autozygosity on common disease risk across the phenotypic spectrum

Autozygosity is associated with rare Mendelian disorders and clinically relevant quantitative traits. We investigated associations between the fraction of the genome in runs of homozygosity (FROH) and common diseases in Genes & Health (n = 23,978 British South Asians), UK Biobank (n = 397,184), and 23andMe. We show that restricting analysis to offspring of first cousins is an effective way of reducing confounding due to social/environmental correlates of FROH. Within this group in G&H+UK Biobank, we found experiment-wide significant associations between FROH and twelve common diseases. We replicated associations with type 2 diabetes (T2D) and post-traumatic stress disorder via within-sibling analysis in 23andMe (median n = 480,282). We estimated that autozygosity due to consanguinity accounts for 5%-18% of T2D cases among British Pakistanis. Our work highlights the possibility of widespread non-additive genetic effects on common diseases and has important implications for global populations with high rates of consanguinity.

Born in Bradford Age of Wonder cohort: A protocol for qualitative longitudinal research

Bradford is multi-ethnic and one of the most deprived districts in the United Kingdom where around a quarter of children live in low-income families. Born in Bradford (BiB) has followed the lives of 13,776 children born in the district between 2007 and 2011. Children in the birth cohort are now entering adolescence, and the next phase of the research - Age of Wonder (AoW) - will be a whole city cohort capturing the experiences of 30,000 adolescents progressing into young adulthood. This protocol focuses on one component of the AoW programme: qualitative longitudinal research (QLR). The study will gather in depth and detailed accounts from a sub-sample of 100 young people across four major research priorities: personal life; social and community life; growing up with difference, and growing up in Bradford. As well as using traditional qualitative methods such as interviews, focus group discussions, and ethnography, we are adopting innovative creative methods including expressions through art, activism, online and digital content, portraits, and critical events. The process of engaging in and co-producing QLR potentially provides a route to empowering young people to shape the narrative of their own lives as well as informing intervention development.

Orthogonal outlier detection and dimension estimation for improved MDS embedding of biological datasets

Conventional dimensionality reduction methods like Multidimensional Scaling (MDS) are sensitive to the presence of orthogonal outliers, leading to significant defects in the embedding. We introduce a robust MDS method, called DeCOr-MDS (Detection and Correction of Orthogonal outliers using MDS), based on the geometry and statistics of simplices formed by data points, that allows to detect orthogonal outliers and subsequently reduce dimensionality. We validate our methods using synthetic datasets, and further show how it can be applied to a variety of large real biological datasets, including cancer image cell data, human microbiome project data and single cell RNA sequencing data, to address the task of data cleaning and visualization.

Disease risk and healthcare utilization among ancestrally diverse groups in the Los Angeles region

An individual's disease risk is affected by the populations that they belong to, due to shared genetics and environmental factors. The study of fine-scale populations in clinical care is important for identifying and reducing health disparities and for developing personalized interventions. To assess patterns of clinical diagnoses and healthcare utilization by fine-scale populations, we leveraged genetic data and electronic medical records from 35,968 patients as part of the UCLA ATLAS Community Health Initiative. We defined clusters of individuals using identity by descent, a form of genetic relatedness that utilizes shared genomic segments arising due to a common ancestor. In total, we identified 376 clusters, including clusters with patients of Afro-Caribbean, Puerto Rican, Lebanese Christian, Iranian Jewish and Gujarati ancestry. Our analysis uncovered 1,218 significant associations between disease diagnoses and clusters and 124 significant associations with specialty visits. We also examined the distribution of pathogenic alleles and found 189 significant alleles at elevated frequency in particular clusters, including many that are not regularly included in population screening efforts. Overall, this work progresses the understanding of health in understudied communities and can provide the foundation for further study into health inequities.

Metabolic drivers of dysglycemia in pregnancy: ethnic-specific GWAS of 146 metabolites and 1-sample Mendelian randomization analyses in a UK multi-ethnic birth cohort

Introduction

Gestational diabetes mellitus (GDM) is the most common pregnancy complication worldwide and is associated with short- and long-term health implications for both mother and child. Prevalence of GDM varies between ethnicities, with South Asians (SAs) experiencing up to three times the risk compared to white Europeans (WEs). Recent evidence suggests that underlying metabolic difference contribute to this disparity, but an investigation of causality is required.

Methods

To address this, we paired metabolite and genomic data to evaluate the causal effect of 146 distinct metabolic characteristics on gestational dysglycemia in SAs and WEs. First, we performed 292 GWASs to identify ethnic-specific genetic variants associated with each metabolite (P ≤ 1 x 10-5) in the Born and Bradford cohort (3688 SA and 3354 WE women). Following this, a one-sample Mendelian Randomisation (MR) approach was applied for each metabolite against fasting glucose and 2-hr post glucose at 26-28 weeks gestation. Additional GWAS and MR on 22 composite measures of metabolite classes were also conducted.

Results

This study identified 15 novel genome-wide significant (GWS) SNPs associated with tyrosine in the FOXN and SLC13A2 genes and 1 novel GWS SNP (currently in no known gene) associated with acetate in SAs. Using MR approach, 14 metabolites were found to be associated with postprandial glucose in WEs, while in SAs a distinct panel of 11 metabolites were identified. Interestingly, in WEs, cholesterols were the dominant metabolite class driving with dysglycemia, while in SAs saturated fatty acids and total fatty acids were most commonly associated with dysglycemia.

Discussion

In summary, we confirm and demonstrate the presence of ethnic-specific causal relationships between metabolites and dysglycemia in mid-pregnancy in a UK population of SA and WE pregnant women. Future work will aim to investigate their biological mechanisms on dysglycemia and translating this work towards ethnically tailored GDM prevention strategies.

Study protocol of DIVERGE, the first genetic epidemiological study of major depressive disorder in Pakistan

INTRODUCTION

Globally, 80% of the burdenof major depressive disorder (MDD) pertains to low- and middle-income countries. Research into genetic and environmental risk factors has the potential to uncover disease mechanisms that may contribute to better diagnosis and treatment of mental illness, yet has so far been largely limited to participants with European ancestry from high-income countries. The DIVERGE study was established to help overcome this gap and investigate genetic and environmental risk factors for MDD in Pakistan.

METHODS

DIVERGE aims to enrol 9000 cases and 4000 controls in hospitals across the country. Here, we provide the rationale for DIVERGE, describe the study protocol and characterise the sample using data from the first 500 cases. Exploratory data analysis is performed to describe demographics, socioeconomic status, environmental risk factors, family history of mental illness and psychopathology.

RESULTS AND DISCUSSION

Many participants had severe depression with 74% of patients who experienced multiple depressive episodes. It was a common practice to seek help for mental health struggles from faith healers and religious leaders. Socioeconomic variables reflected the local context with a large proportion of women not having access to any education and the majority of participants reporting no savings.

CONCLUSION

DIVERGE is a carefully designed case-control study of MDD in Pakistan that captures diverse risk factors. As the largest genetic study in Pakistan, DIVERGE helps address the severe underrepresentation of people from South Asian countries in genetic as well as psychiatric research.

Born in Bradford Age of Wonder cohort: A protocol for qualitative longitudinal research

Born in Bradford (BiB) has followed the lives of 13,776 children born in the district between 2007 and 2011. Children in the birth cohort are now entering adolescence, and the next phase of the research - Age of Wonder (AoW) - will be a whole city cohort capturing the experiences of 30,000 adolescents progressing into young adulthood. This protocol focuses on one component of the AoW programme: qualitative longitudinal research (QLR). The study will gather in depth and detailed accounts from a sub-sample of 100 young people across four major research priorities: personal life; social and community life; growing up with difference, and growing up in Bradford. As well as using traditional qualitative methods such as interviews, focus group discussions, and ethnography, we are adopting innovative creative methods including expressions through art, activism, online and digital content, portraits, and critical events. The process of engaging in and co-producing QLR potentially provides a route to empowering young people to shape the narrative of their own lives as well as informing intervention development.

Unique Metabolic Profiles Associate with Gestational Diabetes and Ethnicity in Low- and High-Risk Women Living in the UK

BACKGROUND

Gestational diabetes mellitus (GDM) is the most common global pregnancy complication; however, prevalence varies substantially between ethnicities, with South Asians (SAs) experiencing up to 3 times the risk of the disease compared with white Europeans (WEs). Factors driving this discrepancy are unclear, although the metabolome is of great interest as GDM is known to be characterized by metabolic dysregulation.

OBJECTIVES

The primary aim was to characterize and compare the metabolic profiles of GDM in SA and WE women (at <28 wk of gestation) from the Born in Bradford (BIB) prospective birth cohort in the United Kingdom.

METHODS

In total, 146 fasting serum metabolites, from 2,668 pregnant WE and 2,671 pregnant SA women (average BMI 26.2 kg/m2, average age 27.3 y) were analyzed using partial least squares discriminatory analyses to characterize GDM status. Linear associations between metabolite values and post-oral glucose tolerance test measures of dysglycemia (fasting glucose and 2 h postglucose) were also examined.

RESULTS

Seven metabolites associated with GDM status in both ethnicities (variable importance in projection ≥1), whereas 6 additional metabolites associated with GDM only in WE women. Unique metabolic profiles were observed in healthy-weight women who later developed GDM, with distinct metabolite patterns identified by ethnicity and BMI status. Of the metabolite values analyzed in relation to dysglycemia, lactate, histidine, apolipoprotein A1, HDL cholesterol, and HDL2 cholesterol associated with decreased glucose concentration, whereas DHA and the diameter of very low-density lipoprotein particles (nm) associated with increased glucose concertation in WE women, and in SAs, albumin alone associated with decreased glucose concentration.

CONCLUSIONS

This study shows that the metabolic risk profile for GDM differs between WE and SA women enrolled in BiB in the United Kingdom. This suggests that etiology of the disease differs between ethnic groups and that ethnic-appropriate prevention strategies may be beneficial.

Limiting distribution of X-chromosomal coalescence times under first-cousin consanguineous mating

By providing additional opportunities for coalescence within families, the presence of consanguineous unions in a population reduces coalescence times relative to non-consanguineous populations. First-cousin consanguinity can take one of six forms differing in the configuration of sexes in the pedigree of the male and female cousins who join in a consanguineous union: patrilateral parallel, patrilateral cross, matrilateral parallel, matrilateral cross, bilateral parallel, and bilateral cross. Considering populations with each of the six types of first-cousin consanguinity individually and a population with a mixture of the four unilateral types, we examine coalescent models of consanguinity. We previously computed, for first-cousin consanguinity models, the mean coalescence time for X-chromosomal loci and the limiting distribution of coalescence times for autosomal loci. Here, we use the separation-of-time-scales approach to obtain the limiting distribution of coalescence times for X-chromosomal loci. This limiting distribution has an instantaneous coalescence probability that depends on the probability that a union is consanguineous; lineages that do not coalesce instantaneously coalesce according to an exponential distribution. We study the effects on the coalescence time distribution of the type of first-cousin consanguinity, showing that patrilateral-parallel and patrilateral-cross consanguinity have no effect on X-chromosomal coalescence time distributions and that matrilateral-parallel consanguinity decreases coalescence times to a greater extent than does matrilateral-cross consanguinity.

The sequences of 150,119 genomes in the UK Biobank

Detailed knowledge of how diversity in the sequence of the human genome affects phenotypic diversity depends on a comprehensive and reliable characterization of both sequences and phenotypic variation. Over the past decade, insights into this relationship have been obtained from whole-exome sequencing or whole-genome sequencing of large cohorts with rich phenotypic data^1,2. Here we describe the analysis of whole-genome sequencing of 150,119 individuals from the UK Biobank³. This constitutes a set of high-quality variants, including 585,040,410 single-nucleotide polymorphisms, representing 7.0% of all possible human single-nucleotide polymorphisms, and 58,707,036 indels. This large set of variants allows us to characterize selection based on sequence variation within a population through a depletion rank score of windows along the genome. Depletion rank analysis shows that coding exons represent a small fraction of regions in the genome subject to strong sequence conservation. We define three cohorts within the UK Biobank: a large British Irish cohort, a smaller African cohort and a South Asian cohort. A haplotype reference panel is provided that allows reliable imputation of most variants carried by three or more sequenced individuals. We identified 895,055 structural variants and 2,536,688 microsatellites, groups of variants typically excluded from large-scale whole-genome sequencing studies. Using this formidable new resource, we provide several examples of trait associations for rare variants with large effects not found previously through studies based on whole-exome sequencing and/or imputation.

Long Runs of Homozygosity Are Correlated with Marriage Preferences across Global Population Samples

Children of consanguineous unions carry long runs of homozygosity (ROH) in their genomes, due to their parents' recent shared ancestry. This increases the burden of recessive disease in populations with high levels of consanguinity and has been heavily studied in some groups. However, there has been little investigation of the broader effect of consanguinity on patterns of genetic variation on a global scale. This study, which collected published genetic data and information about marriage practice from 395 worldwide populations, shows that reported preference for cousin marriage has a detectable association with the distribution of long ROH in this sample, increasing the expected number of ROH longer than 10 cM by a factor of 2.2. Variation in marriage practice and consequent rates of consanguinity are therefore an important aspect of demographic history for the purposes of modeling human genetic variation. However, reported marriage practices explain a relatively small proportion of the variation in ROH distribution, and consequently, population genetic data are only partially informative about cultural preferences.