Elevated genetic risk for multiple sclerosis emerged in steppe pastoralist populations.

Multiple sclerosis (MS) is a neuro-inflammatory and neurodegenerative disease that is most prevalent in Northern Europe. Although it is known that inherited risk for MS is located within or in close proximity to immune-related genes, it is unknown when, where and how this genetic risk originated1. Here, by using a large ancient genome dataset from the Mesolithic period to the Bronze Age2, along with new Medieval and post-Medieval genomes, we show that the genetic risk for MS rose among pastoralists from the Pontic steppe and was brought into Europe by the Yamnaya-related migration approximately 5,000 years ago. We further show that these MS-associated immunogenetic variants underwent positive selection both within the steppe population and later in Europe, probably driven by pathogenic challenges coinciding with changes in diet, lifestyle and population density. This study highlights the critical importance of the Neolithic period and Bronze Age as determinants of modern immune responses and their subsequent effect on the risk of developing MS in a changing environment.

The selection landscape and genetic legacy of ancient Eurasians.

The Holocene (beginning around 12,000 years ago) encompassed some of the most significant changes in human evolution, with far-reaching consequences for the dietary, physical and mental health of present-day populations. Using a dataset of more than 1,600 imputed ancient genomes1, we modelled the selection landscape during the transition from hunting and gathering, to farming and pastoralism across West Eurasia. We identify key selection signals related to metabolism, including that selection at the FADS cluster began earlier than previously reported and that selection near the LCT locus predates the emergence of the lactase persistence allele by thousands of years. We also find strong selection in the HLA region, possibly due to increased exposure to pathogens during the Bronze Age. Using ancient individuals to infer local ancestry tracts in over 400,000 samples from the UK Biobank, we identify widespread differences in the distribution of Mesolithic, Neolithic and Bronze Age ancestries across Eurasia. By calculating ancestry-specific polygenic risk scores, we show that height differences between Northern and Southern Europe are associated with differential Steppe ancestry, rather than selection, and that risk alleles for mood-related phenotypes are enriched for Neolithic farmer ancestry, whereas risk alleles for diabetes and Alzheimer's disease are enriched for Western hunter-gatherer ancestry. Our results indicate that ancient selection and migration were large contributors to the distribution of phenotypic diversity in present-day Europeans.

Population genomics of post-glacial western Eurasia.

Western Eurasia witnessed several large-scale human migrations during the Holocene1-5. Here, to investigate the cross-continental effects of these migrations, we shotgun-sequenced 317 genomes-mainly from the Mesolithic and Neolithic periods-from across northern and western Eurasia. These were imputed alongside published data to obtain diploid genotypes from more than 1,600 ancient humans. Our analyses revealed a 'great divide' genomic boundary extending from the Black Sea to the Baltic. Mesolithic hunter-gatherers were highly genetically differentiated east and west of this zone, and the effect of the neolithization was equally disparate. Large-scale ancestry shifts occurred in the west as farming was introduced, including near-total replacement of hunter-gatherers in many areas, whereas no substantial ancestry shifts happened east of the zone during the same period. Similarly, relatedness decreased in the west from the Neolithic transition onwards, whereas, east of the Urals, relatedness remained high until around 4,000 BP, consistent with the persistence of localized groups of hunter-gatherers. The boundary dissolved when Yamnaya-related ancestry spread across western Eurasia around 5,000 BP, resulting in a second major turnover that reached most parts of Europe within a 1,000-year span. The genetic origin and fate of the Yamnaya have remained elusive, but we show that hunter-gatherers from the Middle Don region contributed ancestry to them. Yamnaya groups later admixed with individuals associated with the Globular Amphora culture before expanding into Europe. Similar turnovers occurred in western Siberia, where we report new genomic data from a 'Neolithic steppe' cline spanning the Siberian forest steppe to Lake Baikal. These prehistoric migrations had profound and lasting effects on the genetic diversity of Eurasian populations.

Genetic continuity and change among the Indigenous peoples of California.

Before the colonial period, California harboured more language variation than all of Europe, and linguistic and archaeological analyses have led to many hypotheses to explain this diversity1. We report genome-wide data from 79 ancient individuals from California and 40 ancient individuals from Northern Mexico dating to 7,400-200 years before present (BP). Our analyses document long-term genetic continuity between people living on the Northern Channel Islands of California and the adjacent Santa Barbara mainland coast from 7,400 years BP to modern Chumash groups represented by individuals who lived around 200 years BP. The distinctive genetic lineages that characterize present-day and ancient people from Northwest Mexico increased in frequency in Southern and Central California by 5,200 years BP, providing evidence for northward migrations that are candidates for spreading Uto-Aztecan languages before the dispersal of maize agriculture from Mexico2-4. Individuals from Baja California share more alleles with the earliest individual from Central California in the dataset than with later individuals from Central California, potentially reflecting an earlier linguistic substrate, whose impact on local ancestry was diluted by later migrations from inland regions1,5. After 1,600 years BP, ancient individuals from the Channel Islands lived in communities with effective sizes similar to those in pre-agricultural Caribbean and Patagonia, and smaller than those on the California mainland and in sampled regions of Mexico.

Genotyping, sequencing and analysis of 140,000 adults from Mexico City.

The Mexico City Prospective Study is a prospective cohort of more than 150,000 adults recruited two decades ago from the urban districts of Coyoacán and Iztapalapa in Mexico City1. Here we generated genotype and exome-sequencing data for all individuals and whole-genome sequencing data for 9,950 selected individuals. We describe high levels of relatedness and substantial heterogeneity in ancestry composition across individuals. Most sequenced individuals had admixed Indigenous American, European and African ancestry, with extensive admixture from Indigenous populations in central, southern and southeastern Mexico. Indigenous Mexican segments of the genome had lower levels of coding variation but an excess of homozygous loss-of-function variants compared with segments of African and European origin. We estimated ancestry-specific allele frequencies at 142 million genomic variants, with an effective sample size of 91,856 for Indigenous Mexican ancestry at exome variants, all available through a public browser. Using whole-genome sequencing, we developed an imputation reference panel that outperforms existing panels at common variants in individuals with high proportions of central, southern and southeastern Indigenous Mexican ancestry. Our work illustrates the value of genetic studies in diverse populations and provides foundational imputation and allele frequency resources for future genetic studies in Mexico and in the United States, where the Hispanic/Latino population is predominantly of Mexican descent.

Northwest African Neolithic initiated by migrants from Iberia and Levant.

In northwestern Africa, lifestyle transitioned from foraging to food production around 7,400 years ago but what sparked that change remains unclear. Archaeological data support conflicting views: (1) that migrant European Neolithic farmers brought the new way of life to North Africa1-3 or (2) that local hunter-gatherers adopted technological innovations4,5. The latter view is also supported by archaeogenetic data6. Here we fill key chronological and archaeogenetic gaps for the Maghreb, from Epipalaeolithic to Middle Neolithic, by sequencing the genomes of nine individuals (to between 45.8- and 0.2-fold genome coverage). Notably, we trace 8,000 years of population continuity and isolation from the Upper Palaeolithic, via the Epipaleolithic, to some Maghrebi Neolithic farming groups. However, remains from the earliest Neolithic contexts showed mostly European Neolithic ancestry. We suggest that farming was introduced by European migrants and was then rapidly adopted by local groups. During the Middle Neolithic a new ancestry from the Levant appears in the Maghreb, coinciding with the arrival of pastoralism in the region, and all three ancestries blend together during the Late Neolithic. Our results show ancestry shifts in the Neolithization of northwestern Africa that probably mirrored a heterogeneous economic and cultural landscape, in a more multifaceted process than observed in other regions.

Polygenic scoring accuracy varies across the genetic ancestry continuum.

Polygenic scores (PGSs) have limited portability across different groupings of individuals (for example, by genetic ancestries and/or social determinants of health), preventing their equitable use1-3. PGS portability has typically been assessed using a single aggregate population-level statistic (for example, R2)4, ignoring inter-individual variation within the population. Here, using a large and diverse Los Angeles biobank5 (ATLAS, n = 36,778) along with the UK Biobank6 (UKBB, n = 487,409), we show that PGS accuracy decreases individual-to-individual along the continuum of genetic ancestries7 in all considered populations, even within traditionally labelled 'homogeneous' genetic ancestries. The decreasing trend is well captured by a continuous measure of genetic distance (GD) from the PGS training data: Pearson correlation of -0.95 between GD and PGS accuracy averaged across 84 traits. When applying PGS models trained on individuals labelled as white British in the UKBB to individuals with European ancestries in ATLAS, individuals in the furthest GD decile have 14% lower accuracy relative to the closest decile; notably, the closest GD decile of individuals with Hispanic Latino American ancestries show similar PGS performance to the furthest GD decile of individuals with European ancestries. GD is significantly correlated with PGS estimates themselves for 82 of 84 traits, further emphasizing the importance of incorporating the continuum of genetic ancestries in PGS interpretation. Our results highlight the need to move away from discrete genetic ancestry clusters towards the continuum of genetic ancestries when considering PGSs.

Ethnic differences in stroke outcomes in Aotearoa New Zealand: A national linkage study.

BACKGROUND: Ethnic differences in post-stroke outcomes have been largely attributed to biological and socioeconomic characteristics resulting in differential risk factor profiles and stroke subtypes, but evidence is mixed. AIMS: This study assessed ethnic differences in stroke outcome and service access in New Zealand (NZ) and explored underlying causes in addition to traditional risk factors. METHODS: This national cohort study used routinely collected health and social data to compare post-stroke outcomes between NZ Europeans, Maori, Pacific Peoples, and Asians, adjusting for differences in baseline characteristics, socioeconomic deprivation, and stroke characteristics. First and principal stroke public hospital admissions during November 2017 to October 2018 were included (N = 6879). Post-stroke unfavorable outcome was defined as being dead, changing residence, or becoming unemployed. RESULTS: In total, 5394 NZ Europeans, 762 Maori, 369 Pacific Peoples, and 354 Asians experienced a stroke during the study period. Median age was 65 years for Maori and Pacific Peoples, and 71 and 79 years for Asians and NZ Europeans, respectively. Compared with NZ Europeans, Maori were more likely to have an unfavorable outcome at all three time-points (odds ratio (OR) = 1.6 (95% confidence interval (CI) = 1.3-1.9); 1.4 (1.2-1.7); 1.4 (1.2-1.7), respectively). Maori had increased odds of death at all time-points (1.7 (1.3-2.1); 1.5 (1.2-1.9); 1.7 (1.3-2.1)), change in residence at 3 and 6 months (1.6 (1.3-2.1); 1.3 (1.1-1.7)), and unemployment at 6 and 12 months (1.5 (1.1-2.1); 1.5 (1.1-2.1)). There was evidence of differences in post-stroke secondary prevention medication by ethnicity. CONCLUSION: We found ethnic disparities in care and outcomes following stroke which were independent of traditional risk factors, suggesting they may be attributable to stroke service delivery rather than patient factors.

Palaeogenomics of Upper Palaeolithic to Neolithic European hunter-gatherers.

Modern humans have populated Europe for more than 45,000 years1,2. Our knowledge of the genetic relatedness and structure of ancient hunter-gatherers is however limited, owing to the scarceness and poor molecular preservation of human remains from that period3. Here we analyse 356 ancient hunter-gatherer genomes, including new genomic data for 116 individuals from 14 countries in western and central Eurasia, spanning between 35,000 and 5,000 years ago. We identify a genetic ancestry profile in individuals associated with Upper Palaeolithic Gravettian assemblages from western Europe that is distinct from contemporaneous groups related to this archaeological culture in central and southern Europe4, but resembles that of preceding individuals associated with the Aurignacian culture. This ancestry profile survived during the Last Glacial Maximum (25,000 to 19,000 years ago) in human populations from southwestern Europe associated with the Solutrean culture, and with the following Magdalenian culture that re-expanded northeastward after the Last Glacial Maximum. Conversely, we reveal a genetic turnover in southern Europe suggesting a local replacement of human groups around the time of the Last Glacial Maximum, accompanied by a north-to-south dispersal of populations associated with the Epigravettian culture. From at least 14,000 years ago, an ancestry related to this culture spread from the south across the rest of Europe, largely replacing the Magdalenian-associated gene pool. After a period of limited admixture that spanned the beginning of the Mesolithic, we find genetic interactions between western and eastern European hunter-gatherers, who were also characterized by marked differences in phenotypically relevant variants.

Religious Afterlife Beliefs Decrease Behavioral Avoidance of Symbols of Mortality.

An astonishing cultural phenomenon is where, far away from or close to a city center, people in different societies localize cemeteries that function as both sites of memory of lost ones and symbols of mortality. Yet a psychological account of such differences in behavioral responses to symbols of mortality is lacking. Across five studies (N = 1,590), we tested a psychological model that religious afterlife beliefs decrease behavioral avoidance of symbols of mortality (BASM) by developing and validating a word-position task for quantifying BASM. We showed evidence that religious believers, including Christians, Muslims, Hindus, and Buddhists, exhibited decreased BASM relative to nonbelievers. We also provide evidence for a causal relationship between religious afterlife beliefs and reduced BASM. Our findings provide new insight into the functional role of religious afterlife beliefs in modulating human avoidance behavior in response to symbols of mortality.

Genetic diversity fuels gene discovery for tobacco and alcohol use.

Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1-4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.

Evolution of immune genes is associated with the Black Death.

Infectious diseases are among the strongest selective pressures driving human evolution1,2. This includes the single greatest mortality event in recorded history, the first outbreak of the second pandemic of plague, commonly called the Black Death, which was caused by the bacterium Yersinia pestis3. This pandemic devastated Afro-Eurasia, killing up to 30-50% of the population4. To identify loci that may have been under selection during the Black Death, we characterized genetic variation around immune-related genes from 206 ancient DNA extracts, stemming from two different European populations before, during and after the Black Death. Immune loci are strongly enriched for highly differentiated sites relative to a set of non-immune loci, suggesting positive selection. We identify 245 variants that are highly differentiated within the London dataset, four of which were replicated in an independent cohort from Denmark, and represent the strongest candidates for positive selection. The selected allele for one of these variants, rs2549794, is associated with the production of a full-length (versus truncated) ERAP2 transcript, variation in cytokine response to Y. pestis and increased ability to control intracellular Y. pestis in macrophages. Finally, we show that protective variants overlap with alleles that are today associated with increased susceptibility to autoimmune diseases, providing empirical evidence for the role played by past pandemics in shaping present-day susceptibility to disease.

A saturated map of common genetic variants associated with human height.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Stroke genetics informs drug discovery and risk prediction across ancestries.

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.

African-specific molecular taxonomy of prostate cancer.

Prostate cancer is characterized by considerable geo-ethnic disparity. African ancestry is a significant risk factor, with mortality rates across sub-Saharan Africa of 2.7-fold higher than global averages1. The contributing genetic and non-genetic factors, and associated mutational processes, are unknown2,3. Here, through whole-genome sequencing of treatment-naive prostate cancer samples from 183 ancestrally (African versus European) and globally distinct patients, we generate a large cancer genomics resource for sub-Saharan Africa, identifying around 2 million somatic variants. Significant African-ancestry-specific findings include an elevated tumour mutational burden, increased percentage of genome alteration, a greater number of predicted damaging mutations and a higher total of mutational signatures, and the driver genes NCOA2, STK19, DDX11L1, PCAT1 and SETBP1. Examining all somatic mutational types, we describe a molecular taxonomy for prostate cancer differentiated by ancestry and defined as global mutational subtypes (GMS). By further including Chinese Asian data, we confirm that GMS-B (copy-number gain) and GMS-D (mutationally noisy) are specific to African populations, GMS-A (mutationally quiet) is universal (all ethnicities) and the African-European-restricted subtype GMS-C (copy-number losses) predicts poor clinical outcomes. In addition to the clinical benefit of including individuals of African ancestry, our GMS subtypes reveal different evolutionary trajectories and mutational processes suggesting that both common genetic and environmental factors contribute to the disparity between ethnicities. Analogous to gene-environment interaction-defined here as a different effect of an environmental surrounding in people with different ancestries or vice versa-we anticipate that GMS subtypes act as a proxy for intrinsic and extrinsic mutational processes in cancers, promoting global inclusion in landmark studies.

Dairying, diseases and the evolution of lactase persistence in Europe.

In European and many African, Middle Eastern and southern Asian populations, lactase persistence (LP) is the most strongly selected monogenic trait to have evolved over the past 10,000 years1. Although the selection of LP and the consumption of prehistoric milk must be linked, considerable uncertainty remains concerning their spatiotemporal configuration and specific interactions2,3. Here we provide detailed distributions of milk exploitation across Europe over the past 9,000 years using around 7,000 pottery fat residues from more than 550 archaeological sites. European milk use was widespread from the Neolithic period onwards but varied spatially and temporally in intensity. Notably, LP selection varying with levels of prehistoric milk exploitation is no better at explaining LP allele frequency trajectories than uniform selection since the Neolithic period. In the UK Biobank4,5 cohort of 500,000 contemporary Europeans, LP genotype was only weakly associated with milk consumption and did not show consistent associations with improved fitness or health indicators. This suggests that other reasons for the beneficial effects of LP should be considered for its rapid frequency increase. We propose that lactase non-persistent individuals consumed milk when it became available but, under conditions of famine and/or increased pathogen exposure, this was disadvantageous, driving LP selection in prehistoric Europe. Comparison of model likelihoods indicates that population fluctuations, settlement density and wild animal exploitation-proxies for these drivers-provide better explanations of LP selection than the extent of milk exploitation. These findings offer new perspectives on prehistoric milk exploitation and LP evolution.

Recessive Genome-Wide Meta-analysis Illuminates Genetic Architecture of Type 2 Diabetes.

Most genome-wide association studies (GWAS) of complex traits are performed using models with additive allelic effects. Hundreds of loci associated with type 2 diabetes have been identified using this approach. Additive models, however, can miss loci with recessive effects, thereby leaving potentially important genes undiscovered. We conducted the largest GWAS meta-analysis using a recessive model for type 2 diabetes. Our discovery sample included 33,139 case subjects and 279,507 control subjects from 7 European-ancestry cohorts, including the UK Biobank. We identified 51 loci associated with type 2 diabetes, including five variants undetected by prior additive analyses. Two of the five variants had minor allele frequency of <5% and were each associated with more than a doubled risk in homozygous carriers. Using two additional cohorts, FinnGen and a Danish cohort, we replicated three of the variants, including one of the low-frequency variants, rs115018790, which had an odds ratio in homozygous carriers of 2.56 (95% CI 2.05-3.19; P = 1 × 10-16) and a stronger effect in men than in women (for interaction, P = 7 × 10-7). The signal was associated with multiple diabetes-related traits, with homozygous carriers showing a 10% decrease in LDL cholesterol and a 20% increase in triglycerides; colocalization analysis linked this signal to reduced expression of the nearby PELO gene. These results demonstrate that recessive models, when compared with GWAS using the additive approach, can identify novel loci, including large-effect variants with pathophysiological consequences relevant to type 2 diabetes.

CCR5Δ32 in Brazil: Impacts of a European Genetic Variant on a Highly Admixed Population.

The genetic background of Brazilians encompasses Amerindian, African, and European components as a result of the colonization of an already Amerindian inhabited region by Europeans, associated to a massive influx of Africans. Other migratory flows introduced into the Brazilian population genetic components from Asia and the Middle East. Currently, Brazil has a highly admixed population and, therefore, the study of genetic factors in the context of health or disease in Brazil is a challenging and remarkably interesting subject. This phenomenon is exemplified by the genetic variant CCR5Δ32, a 32 base-pair deletion in the CCR5 gene. CCR5Δ32 originated in Europe, but the time of origin as well as the selective pressures that allowed the maintenance of this variant and the establishment of its current frequencies in the different human populations is still a field of debates. Due to its origin, the CCR5Δ32 allele frequency is high in European-derived populations (~10%) and low in Asian and African native human populations. In Brazil, the CCR5Δ32 allele frequency is intermediate (4-6%) and varies on the Brazilian States, depending on the migratory history of each region. CCR5 is a protein that regulates the activity of several immune cells, also acting as the main HIV-1 co-receptor. The CCR5 expression is influenced by CCR5Δ32 genotypes. No CCR5 expression is observed in CCR5Δ32 homozygous individuals. Thus, the CCR5Δ32 has particular effects on different diseases. At the population level, the effect that CCR5Δ32 has on European populations may be different than that observed in highly admixed populations. Besides less evident due to its low frequency in admixed groups, the effect of the CCR5Δ32 variant may be affected by other genetic traits. Understanding the effects of CCR5Δ32 on Brazilians is essential to predict the potential use of pharmacological CCR5 modulators in Brazil. Therefore, this study reviews the impacts of the CCR5Δ32 on the Brazilian population, considering infectious diseases, inflammatory conditions, and cancer. Finally, this article provides a general discussion concerning the impacts of a European-derived variant, the CCR5Δ32, on a highly admixed population.

Cultural differences in social support seeking: The mediating role of empathic concern.

Prior research has found that East Asians are less willing than Westerners to seek social support in times of need. What factors account for this cultural difference? Whereas previous research has examined the mediating effect of relational concern, we predicted that empathic concern, which refers to feeling sympathy and concern for people in need and varies by individuals from different cultures, would promote support seeking. We tested the prediction in two studies. In Study 1, European Canadians reported higher empathic concern and a higher frequency of support seeking, compared to the Japanese participants. As predicted, cultural differences in social support seeking were influenced by empathic concern. In Study 2, both empathic concern and relational concern mediated cultural differences in support seeking. Japanese with lower empathic concern but higher relational concern were more reluctant than European Americans to seek social support during stressful times. Finally, loneliness, which was more prevalent among the Japanese than among the European Americans, was partially explained by social support seeking.

Exome sequencing and analysis of 454,787 UK Biobank participants.

A major goal in human genetics is to use natural variation to understand the phenotypic consequences of altering each protein-coding gene in the genome. Here we used exome sequencing1 to explore protein-altering variants and their consequences in 454,787 participants in the UK Biobank study2. We identified 12 million coding variants, including around 1 million loss-of-function and around 1.8 million deleterious missense variants. When these were tested for association with 3,994 health-related traits, we found 564 genes with trait associations at P ≤ 2.18 × 10-11. Rare variant associations were enriched in loci from genome-wide association studies (GWAS), but most (91%) were independent of common variant signals. We discovered several risk-increasing associations with traits related to liver disease, eye disease and cancer, among others, as well as risk-lowering associations for hypertension (SLC9A3R2), diabetes (MAP3K15, FAM234A) and asthma (SLC27A3). Six genes were associated with brain imaging phenotypes, including two involved in neural development (GBE1, PLD1). Of the signals available and powered for replication in an independent cohort, 81% were confirmed; furthermore, association signals were generally consistent across individuals of European, Asian and African ancestry. We illustrate the ability of exome sequencing to identify gene-trait associations, elucidate gene function and pinpoint effector genes that underlie GWAS signals at scale.