Correlation between Genetic and Geographic Structure in Europe

An 8-SNP LDL Cholesterol Polygenic Score: Associations with Cardiovascular Risk Traits, Familial Hypercholesterolemia Phenotype, and Premature Coronary Heart Disease in Central Romania

Familial hypercholesterolemia (FH) is the most significant inherited risk factor for coronary heart disease (CHD). Current guidelines focus on monogenic FH, but the polygenic form is more common and less understood. This study aimed to assess the clinical utility of an 8-SNP LDLC polygenic score in a central Romanian cohort. The cohort included 97 healthy controls and 125 patients with premature (P)CHD. The weighted LDLC polygenic risk score (wPRS) was analyzed for associations with relevant phenotypic traits, PCHD risk, and clinical FH diagnosis. The wPRS positively correlated with LDLC and DLCN scores, and LDLC concentrations could be predicted by wPRS. A trend of increasing LDLC and DLCN scores with wPRS deciles was observed. A +1 SD increase in wPRS was associated with a 36% higher likelihood of having LDLC > 190 mg/dL and increases in LDLC (+0.20 SD), DLCN score (+0.16 SD), and BMI (+0.15 SD), as well as a decrease in HDLC (-0.14 SD). Although wPRS did not predict PCHD across the entire spectrum of values, individuals above the 90th percentile were three times more likely to have PCHD compared to those within the 10th or 20th percentiles. Additionally, wPRS > 45th percentile identified "definite" clinical FH (DLCN score > 8) with 100% sensitivity and 45% specificity. The LDLC polygenic score correlates with key phenotypic traits, and individuals with high scores are more likely to have PCHD. Implementing this genetic tool may enhance risk prediction and patient stratification. These findings, the first of their kind in Romania, are consistent with the existing literature.

The Spectrum of Disease-Associated Alleles in Countries with a Predominantly Slavic Population

There are more than 260 million people of Slavic descent worldwide, who reside mainly in Eastern Europe but also represent a noticeable share of the population in the USA and Canada. Slavic populations, particularly Eastern Slavs and some Western Slavs, demonstrate a surprisingly high degree of genetic homogeneity, and, consequently, remarkable contribution of recurrent alleles associated with hereditary diseases. Along with pan-European pathogenic variants with clearly elevated occurrence in Slavic people (e.g., ATP7B c.3207C>A and PAH c.1222C>T), there are at least 52 pan-Slavic germ-line mutations (e.g., NBN c.657_661del and BRCA1 c.5266dupC) as well as several disease-predisposing alleles characteristic of the particular Slavic communities (e.g., Polish SDHD c.33C>A and Russian ARSB c.1562G>A variants). From a clinical standpoint, Slavs have some features of a huge founder population, thus providing a unique opportunity for efficient genetic studies.

Putative protective genomic variation in the Lithuanian population

Genomic effect variants associated with survival and protection against complex diseases vary between populations due to microevolutionary processes. The aim of this study was to analyse diversity and distribution of effect variants in a context of potential positive selection. In total, 475 individuals of Lithuanian origin were genotyped using high-throughput scanning and/or sequencing technologies. Allele frequency analysis for the pre-selected effect variants was performed using the catalogue of single nucleotide polymorphisms. Comparison of the pre-selected effect variants with variants in primate species was carried out to ascertain which allele was derived and potentially of protective nature. Recent positive selection analysis was performed to verify this protective effect. Four variants having significantly different frequencies compared to European populations were identified while two other variants reached borderline significance. Effect variant in SLC30A8 gene may potentially protect against type 2 diabetes. The existing paradox of high rates of type 2 diabetes in the Lithuanian population and the relatively high frequencies of potentially protective genome variants against it indicate a lack of knowledge about the interactions between environmental factors, regulatory regions, and other genome variation. Identification of effect variants is a step towards better understanding of the microevolutionary processes, etiopathogenetic mechanisms, and personalised medicine.

Differentiated adaptative genetic architecture and language-related demographical history in South China inferred from 619 genomes from 56 populations

BACKGROUND

The underrepresentation of human genomic resources from Southern Chinese populations limited their health equality in the precision medicine era and complete understanding of their genetic formation, admixture, and adaptive features. Besides, linguistical and genetic evidence supported the controversial hypothesis of their origin processes. One hotspot case was from the Chinese Guangxi Pinghua Han people (GPH), whose language was significantly similar to Southern Chinese dialects but whose uniparental gene pool was phylogenetically associated with the indigenous Tai-Kadai (TK) people. Here, we analyzed genome-wide SNP data in 619 people from four language families and 56 geographically different populations, in which 261 people from 21 geographically distinct populations were first reported here.

RESULTS

We identified significant population stratification among ethnolinguistically diverse Guangxi populations, suggesting their differentiated genetic origin and admixture processes. GPH shared more alleles related to Zhuang than Southern Han Chinese but received more northern ancestry relative to Zhuang. Admixture models and estimates of genetic distances showed that GPH had a close genetic relationship with geographically close TK compared to Northern Han Chinese, supporting their admixture origin hypothesis. Further admixture time and demographic history reconstruction supported GPH was formed via admixture between Northern Han Chinese and Southern TK people. We identified robust signatures associated with lipid metabolisms, such as fatty acid desaturases (FADS) and medically relevant loci associated with Mendelian disorder (GJB2) and complex diseases. We also explored the shared and unique selection signatures of ethnically different but linguistically related Guangxi lineages and found some shared signals related to immune and malaria resistance.

CONCLUSIONS

Our genetic analysis illuminated the language-related fine-scale genetic structure and provided robust genetic evidence to support the admixture hypothesis that can explain the pattern of observed genetic diversity and formation of GPH. This work presented one comprehensive analysis focused on the population history and demographical adaptative process, which provided genetic evidence for personal health management and disease risk prediction models from Guangxi people. Further large-scale whole-genome sequencing projects would provide the entire landscape of southern Chinese genomic diversity and their contributions to human health and disease traits.

Biogeographic Perspectives on Human Genetic Diversification

Modern humans originated in Africa 300,000 yr ago, and before leaving their continent of origin, they underwent a process of intense diversification involving complex demographic dynamics. Upon exiting Africa, different populations emerged on the four other inhabited continents, shaped by the interplay of various evolutionary processes, such as migrations, founder effects, and natural selection. Within each region, continental populations, in turn, diversified and evolved almost independently for millennia. As a backdrop to this diversification, introgressions from archaic species contributed to establishing different patterns of genetic diversity in different geographic regions, reshaping our understanding of our species' variability. With the increasing availability of genomic data, it has become possible to delineate the subcontinental human population structure precisely. However, the bias toward the genomic research focused on populations from the global North has limited our understanding of the real diversity of our species and the processes and events that guided different human groups throughout their evolutionary history. This perspective is part of a series of articles celebrating 40 yr since our journal, Molecular Biology and Evolution, was founded (Russo et al. 2024). The perspective is accompanied by virtual issues, a selection of papers on human diversification published by Genome Biology and Evolution and Molecular Biology and Evolution.

Archaic Introgression Shaped Human Circadian Traits

When the ancestors of modern Eurasians migrated out of Africa and interbred with Eurasian archaic hominins, namely, Neanderthals and Denisovans, DNA of archaic ancestry integrated into the genomes of anatomically modern humans. This process potentially accelerated adaptation to Eurasian environmental factors, including reduced ultraviolet radiation and increased variation in seasonal dynamics. However, whether these groups differed substantially in circadian biology and whether archaic introgression adaptively contributed to human chronotypes remain unknown. Here, we traced the evolution of chronotype based on genomes from archaic hominins and present-day humans. First, we inferred differences in circadian gene sequences, splicing, and regulation between archaic hominins and modern humans. We identified 28 circadian genes containing variants with potential to alter splicing in archaics (e.g., CLOCK, PER2, RORB, and RORC) and 16 circadian genes likely divergently regulated between present-day humans and archaic hominins, including RORA. These differences suggest the potential for introgression to modify circadian gene expression. Testing this hypothesis, we found that introgressed variants are enriched among expression quantitative trait loci for circadian genes. Supporting the functional relevance of these regulatory effects, we found that many introgressed alleles have associations with chronotype. Strikingly, the strongest introgressed effects on chronotype increase morningness, consistent with adaptations to high latitude in other species. Finally, we identified several circadian loci with evidence of adaptive introgression or latitudinal clines in allele frequency. These findings identify differences in circadian gene regulation between modern humans and archaic hominins and support the contribution of introgression via coordinated effects on variation in human chronotype.

Complete Mitochondrial DNA Genome Variation in the Swedish Population

The development of complete mitochondrial genome (mitogenome) reference data for inclusion in publicly available population databases is currently underway, and the generation of more high-quality mitogenomes will only enhance the statistical power of this forensically useful locus. To characterize mitogenome variation in Sweden, the mitochondrial DNA (mtDNA) reads from the SweGen whole genome sequencing (WGS) dataset were analyzed. To overcome the interference from low-frequency nuclear mtDNA segments (NUMTs), a 10% variant frequency threshold was applied for the analysis. In total, 934 forensic-quality mitogenome haplotypes were characterized. Almost 45% of the SweGen haplotypes belonged to haplogroup H. Nearly all mitogenome haplotypes (99.1%) were assigned to European haplogroups, which was expected based on previous mtDNA studies of the Swedish population. There were signature northern Swedish and Finnish haplogroups observed in the dataset (e.g., U5b1, W1a), consistent with the nuclear DNA analyses of the SweGen data. The complete mitogenome analysis resulted in high haplotype diversity (0.9996) with a random match probability of 0.15%. Overall, the SweGen mitogenomes provide a large mtDNA reference dataset for the Swedish population and also contribute to the effort to estimate global mitogenome haplotype frequencies.

Pervasive Sharing of Causal Genetic Risk Factors Contributes to Clinical and Molecular Overlap between Sjögren's Disease and Systemic Lupus Erythematosus

SjD (Sjögren's Disease) and SLE (Systemic Lupus Erythematosus) are similar diseases. There is extensive overlap between the two in terms of both clinical features and pathobiologic mechanisms. Shared genetic risk is a potential explanation of this overlap. In this study, we evaluated whether these diseases share causal genetic risk factors. We compared the causal genetic risk for SLE and SjD using three complementary approaches. First, we examined the published GWAS results for these two diseases by analyzing the predicted causal gene protein-protein interaction networks of both diseases. Since this method does not account for overlapping risk intervals, we examined whether such intervals also overlap. Third, we used two-sample Mendelian randomization (two sample MR) using GWAS summary statistics to determine whether risk variants for SLE are causal for SjD and vice versa. We found that both the putative causal genes and the genomic risk intervals for SLE and SjD overlap 28- and 130-times more than expected by chance (p < 1.1 × 10-24 and p < 1.1 × 10-41, respectively). Further, two sample MR analysis confirmed that alone or in aggregate, SLE is likely causal for SjD and vice versa. [SjD variants predicting SLE: OR = 2.56; 95% CI (1.98-3.30); p < 1.4 × 10-13, inverse-variance weighted; SLE variants predicting SjD: OR = 1.36; 95% CI (1.26-1.47); p < 1.6 × 10-11, inverse-variance weighted]. Notably, some variants have disparate impact in terms of effect size across disease states. Overlapping causal genetic risk factors were found for both diseases using complementary approaches. These observations support the hypothesis that shared genetic factors drive the clinical and pathobiologic overlap between these diseases. Our study has implications for both differential diagnosis and future genetic studies of these two conditions.

Exposure to systemic antibiotics in outpatient care and the risk of multiple sclerosis

BACKGROUND

Infections, early life exposures and the microbiome have been associated with the aetiology of multiple sclerosis (MS). Data on any possible roles of antibiotics is scarce and conflicting.

OBJECTIVE

The objective of this study was to investigate associations between outpatient systemic antibiotic exposure and the risk of MS in a nationwide case-control setting.

METHODS

Patients with MS were identified from the nation MS registry and their exposure to antibiotics was compared with that of persons without MS, provided by the national census authority. Antibiotic exposure was investigated using the national prescription database and analyzed by Anatomical Therapeutic Chemical (ATC) category.

RESULTS

Among the 1830 patients with MS and 12765 control persons, there were no associations between exposure to antibiotics in childhood (5-9 years) or adolescence (10-19 years) and the subsequent risk of MS. There was also no association between antibiotic exposure 1-6 years before disease onset and the risk of MS, save for exposure to fluoroquinolones in women (odds ratio: 1.28; 95% confidence interval: 1.03, 1.60; p = 0.028) which is probably associated with the increased infection burden in the MS prodrome.

CONCLUSION

Use of systemic prescription antibiotics was not associated with subsequent MS risk.

Methods for Assessing Population Relationships and History Using Genomic Data

Genetic data contain a record of our evolutionary history. The availability of large-scale datasets of human populations from various geographic areas and timescales, coupled with advances in the computational methods to analyze these data, has transformed our ability to use genetic data to learn about our evolutionary past. Here, we review some of the widely used statistical methods to explore and characterize population relationships and history using genomic data. We describe the intuition behind commonly used approaches, their interpretation, and important limitations. For illustration, we apply some of these techniques to genome-wide autosomal data from 929 individuals representing 53 worldwide populations that are part of the Human Genome Diversity Project. Finally, we discuss the new frontiers in genomic methods to learn about population history. In sum, this review highlights the power (and limitations) of DNA to infer features of human evolutionary history, complementing the knowledge gleaned from other disciplines, such as archaeology, anthropology, and linguistics.

Genetic and geographic influence on phenotypic variation in European sarcoidosis patients

Introduction

Sarcoidosis is a highly variable disease in terms of organ involvement, type of onset and course. Associations of genetic polymorphisms with sarcoidosis phenotypes have been observed and suggest genetic signatures.

Methods

After obtaining a positive vote of the competent ethics committee we genotyped 1909 patients of the deeply phenotyped Genetic-Phenotype Relationship in Sarcoidosis (GenPhenReSa) cohort of 31 European centers in 12 countries with 116 potentially disease-relevant single-nucleotide polymorphisms (SNPs). Using a meta-analysis, we investigated the association of relevant phenotypes (acute vs. sub-acute onset, phenotypes of organ involvement, specific organ involvements, and specific symptoms) with genetic markers. Subgroups were built on the basis of geographical, clinical and hospital provision considerations.

Results

In the meta-analysis of the full cohort, there was no significant genetic association with any considered phenotype after correcting for multiple testing. In the largest sub-cohort (Serbia), we confirmed the known association of acute onset with TNF and reported a new association of acute onset an HLA polymorphism. Multi-locus models with sets of three SNPs in different genes showed strong associations with the acute onset phenotype in Serbia and Lublin (Poland) demonstrating potential region-specific genetic links with clinical features, including recently described phenotypes of organ involvement.

Discussion

The observed associations between genetic variants and sarcoidosis phenotypes in subgroups suggest that gene-environment-interactions may influence the clinical phenotype. In addition, we show that two different sets of genetic variants are permissive for the same phenotype of acute disease only in two geographic subcohorts pointing to interactions of genetic signatures with different local environmental factors. Our results represent an important step towards understanding the genetic architecture of sarcoidosis.

Inferring human neutral genetic variation from craniodental phenotypes

There is a growing consensus that global patterns of modern human cranial and dental variation are shaped largely by neutral evolutionary processes, suggesting that craniodental features can be used as reliable proxies for inferring population structure and history in bioarchaeological, forensic, and paleoanthropological contexts. However, there is disagreement on whether certain types of data preserve a neutral signature to a greater degree than others. Here, we address this unresolved question and systematically test the relative neutrality of four standard metric and nonmetric craniodental data types employing an extensive computational genotype-phenotype comparison across modern populations from around the world. Our computation draws on the largest existing data sets currently available, while accounting for geographically structured environmental variation, population sampling uncertainty, disparate numbers of phenotypic variables, and stochastic variation inherent to a neutral model of evolution. Our results reveal that the four data types differentially capture neutral genomic variation, with highest signals preserved in dental nonmetric and cranial metric data, followed by cranial nonmetric and dental metric data. Importantly, we demonstrate that combining all four data types together maximizes the neutral genetic signal compared with using them separately, even with a limited number of phenotypic variables. We hypothesize that this reflects a lower level of genetic integration through pleiotropy between, compared to within, the four data types, effectively forming four different modules associated with relatively independent sets of loci. Therefore, we recommend that future craniodental investigations adopt holistic combined data approaches, allowing for more robust inferences about underlying neutral genetic variation.

Adult-Onset Neuroepidemiology in Finland: Lessons to Learn and Work to Do

Finland is a relatively small genetic isolate with a genetically non-homogenous population. Available Finnish data on neuroepidemiology of adult-onset disorders are limited, and this paper describes the conclusions that can be drawn and their implications. Apparently, Finnish people have a (relatively) high risk of developing Unverricht-Lundborg disease (EPM1), Multiple Sclerosis (MS), Amyotrophic Lateral Sclerosis (ALS), Spinal muscular atrophy, Jokela type (SMAJ) and adult-onset dystonia. On the other hand, some disorders, such as Friedreich's ataxia (FRDA) and Wilson's disease (WD), are almost absent or completely absent in the population. Valid and timely data concerning even many common disorders, such as stroke, migraine, neuropathy, Alzheimer's disease and Parkinson's disease, are unavailable, and there are virtually no data on many less-common neurological disorders, such as neurosarcoidosis or autoimmune encephalitides. There also appear to be marked regional differences in the incidence and prevalence of many diseases, suggesting that non-granular nationwide data may be misleading in many cases. Concentrated efforts to advance neuroepidemiological research in the country would be of clinical, administrative and scientific benefit, but currently, all progress is blocked by administrative and financial obstacles.

Cross-tissue omics analysis discovers ten adipose genes encoding secreted proteins in obesity-related non-alcoholic fatty liver disease

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is a fast-growing, underdiagnosed, epidemic. We hypothesise that obesity-related inflammation compromises adipose tissue functions, preventing efficient fat storage, and thus driving ectopic fat accumulation into the liver.

METHODS

To identify adipose-based mechanisms and potential serum biomarker candidates (SBCs) for NAFLD, we utilise dual-tissue RNA-sequencing (RNA-seq) data in adipose tissue and liver, paired with histology-based NAFLD diagnosis, from the same individuals in a cohort of obese individuals. We first scan for genes that are differentially expressed (DE) for NAFLD in obese individuals' subcutaneous adipose tissue but not in their liver; encode proteins secreted to serum; and show preferential adipose expression. Then the identified genes are filtered to key adipose-origin NAFLD genes by best subset analysis, knockdown experiments during human preadipocyte differentiation, recombinant protein treatment experiments in human liver HepG2 cells, and genetic analysis.

FINDINGS

We discover a set of genes, including 10 SBCs, that may modulate NAFLD pathogenesis by impacting adipose tissue function. Based on best subset analysis, we further follow-up on two SBCs CCDC80 and SOD3 by knockdown in human preadipocytes and subsequent differentiation experiments, which show that they modulate crucial adipogenesis genes, LPL, SREBPF1, and LEP. We also show that treatment of the liver HepG2 cells with the CCDC80 and SOD3 recombinant proteins impacts genes related to steatosis and lipid processing, including PPARA, NFE2L2, and RNF128. Finally, utilizing the adipose NAFLD DE gene cis-regulatory variants associated with serum triglycerides (TGs) in extensive genome-wide association studies (GWASs), we demonstrate a unidirectional effect of serum TGs on NAFLD with Mendelian Randomization (MR) analysis. We also demonstrate that a single SNP regulating one of the SBC genes, rs2845885, produces a significant MR result by itself. This supports the conclusion that genetically regulated adipose expression of the NAFLD DE genes may contribute to NAFLD through changes in serum TG levels.

INTERPRETATION

Our results from the dual-tissue transcriptomics screening improve the understanding of obesity-related NAFLD by providing a targeted set of 10 adipose tissue-active genes as new serum biomarker candidates for the currently grossly underdiagnosed fatty liver disease.

FUNDING

The work was supported by NIH grants R01HG010505 and R01DK132775. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. The KOBS study (J. P.) was supported by the Finnish Diabetes Research Foundation, Kuopio University Hospital Project grant (EVO/VTR grants 2005-2019), and the Academy of Finland grant (Contract no. 138006). This study was funded by the European Research Council under the European Union's Horizon 2020 research and innovation program (Grant No. 802825 to M. U. K.). K. H. P. was funded by the Academy of Finland (grant numbers 272376, 266286, 314383, and 335443), the Finnish Medical Foundation, Gyllenberg Foundation, Novo Nordisk Foundation (grant numbers NNF10OC1013354, NNF17OC0027232, and NNF20OC0060547), Finnish Diabetes Research Foundation, Finnish Foundation for Cardiovascular Research, University of Helsinki, and Helsinki University Hospital and Government Research Funds. I. S. was funded by the Instrumentarium Science Foundation. Personal grants to U. T. A. were received from the Matti and Vappu Maukonen Foundation, Ella och Georg Ehrnrooths Stiftelse and the Finnish Foundation for Cardiovascular Research.

Clinical spectrum and genotype-phenotype associations in Finnish patients with Wilson's disease

Genotype-phenotype correlation data covering all ages of Wilson's disease onset in Caucasian patients are limited. We therefore analyzed genotype-phenotype correlations in a retrospective cohort of Finnish patients. Six homozygous (HoZ) and 11 compound heterozygous (CoHZ) patients were included. There were no differences in the presence/absence of hepatic, neurological, psychiatric or any symptoms at diagnosis (p > 0.30 for all) between HoZ and CoHZ patients, but HoZ patients had an earlier age of diagnosis (median 6.7 versus 34.5; p = 0.003). Severe liver affliction was almost exclusively associated with the p.H1069Q variant. Patients with p.H1069Q had a later mean age of diagnosis (30.2 ± 11.6 vs. 8.7 ± 4.9 years; p < 0.001) compared to those without. There were no differences in the presence/absence of hepatic, neurological, psychiatric or any symptoms at diagnosis between p.H1069Q-positive and p.H1069Q-negative patients (p > 0.54 for all). These results suggest that population-specific factors may partly explain the high clinical variability of Wilson's disease.

The power of geohistorical boundaries for modeling the genetic background of human populations: The case of the rural catalan Pyrenees

The genetic variation of the European population at a macro-geographic scale follows genetic gradients which reflect main migration events. However, less is known about factors affecting mating patterns at a micro-geographic scale. In this study we have analyzed 726,718 autosomal single nucleotide variants in 435 individuals from the catalan Pyrenees covering around 200 km of a vast and abrupt region in the north of the Iberian Peninsula, for which we have information about the geographic origin of all grand-parents and parents. At a macro-geographic scale, our analyses recapitulate the genetic gradient observed in Spain. However, we also identified the presence of micro-population substructure among the sampled individuals. Such micro-population substructure does not correlate with geographic barriers such as the expected by the orography of the considered region, but by the bishoprics present in the covered geographic area. These results support that, on top of main human migrations, long ongoing socio-cultural factors have also shaped the genetic diversity observed at rural populations.

APOE Allele Frequency in Southern Greece: Exploring the Role of Geographical Gradient in the Greek Population

BACKGROUND

the apolipoprotein e4 allele (APOE4) constitutes an established genetic risk factor for Alzheimer's Disease Dementia (ADD). We aimed to explore the frequency of the APOE isoforms in the Greek population of Southern Greece.

METHODS

peripheral blood from 175 Greek AD patients, 113 with mild cognitive impairment (MCI), and 75 healthy individuals. DNA isolation was performed with a High Pure PCR Template Kit (Roche), followed by amplification with a real-time qPCR kit (TIB MolBiol) in Roche's Light Cycler PCR platform.

RESULTS

APOE4 allele frequency was 20.57% in the ADD group, 17.69% in the MCI group, and 6.67% in the control group. APOE3/3 homozygosity was the most common genotype, while the frequency of APOE4/4 homozygosity was higher in the AD group (8.60%). APOE4 carrier status was associated with higher odds for ADD and MCI (OR: 4.49, 95% CI: [1.90-10.61] and OR: 3.82, 95% CI: [1.59-9.17], respectively).

CONCLUSION

this study examines the APOE isoforms and is the first to report a higher APOE frequency in MCI compared with healthy controls in southern Greece. Importantly, we report the occurrence of the APOE4 allele, related to ADD, as amongst the lowest globally reported, even within the nation, thus enhancing the theory of ethnicity and latitude contribution.

The kringle IV type 2 domain variant 4925G>A causes the elusive association signal of the LPA pentanucleotide repeat

Lipoprotein(a) [Lp(a)] concentrations are regulated by the LPA gene mainly via the large kringle IV-type 2 (KIV-2) copy number variation and multiple causal variants. Early studies suggested an effect of long pentanucleotide repeat (PNR) alleles (10 and 11 repeats, PNR10 and PNR11) in the LPA promoter on gene transcription and found an association with lower Lp(a). Subsequent in vitro studies showed no effects on mRNA transcription, but the association with strongly decreased Lp(a) remained consistent. We investigated the isolated and combined effect of PNR10, PNR11, and the frequent splice site variant KIV-2 4925G>A on Lp(a) concentrations in the Cooperative Health Research in the Region of Augsburg F4 study by multiple quantile regression in single-SNP and joint models. Data on Lp(a), apolipoprotein(a) Western blot isoforms, and variant genotypes were available for 2,858 individuals. We found a considerable linkage disequilibrium between KIV-2 4925G>A and the alleles PNR10 and PNR11. In single-variant analysis adjusted for age, sex, and the shorter apo(a) isoform, we determined that both PNR alleles were associated with a highly significant Lp(a) decrease (PNR10: β = -14.43 mg/dl, 95% CI: -15.84, -13.02, P = 3.33e-84; PNR11: β = -17.21 mg/dl, 95% CI: -20.19, -14.23, P = 4.01e-29). However, a joint model, adjusting the PNR alleles additionally for 4925G>A, abolished the effect on Lp(a) (PNR10: β = +0.44 mg/dl, 95% CI: -1.73, 2.60, P = 0.69; PNR11: β = -1.52 mg/dl, 95% CI: -6.05, 3.00, P = 0.51). Collectively, we conclude that the previously reported Lp(a) decrease observed in pentanucleotide alleles PNR10 or PNR11 carriers results from a linkage disequilibrium with the frequent splicing mutation KIV-2 4925G>A.

Including diverse and admixed populations in genetic epidemiology research

The inclusion of ancestrally diverse participants in genetic studies can lead to new discoveries and is important to ensure equitable health care benefit from research advances. Here, members of the Ethical, Legal, Social, Implications (ELSI) committee of the International Genetic Epidemiology Society (IGES) offer perspectives on methods and analysis tools for the conduct of inclusive genetic epidemiology research, with a focus on admixed and ancestrally diverse populations in support of reproducible research practices. We emphasize the importance of distinguishing socially defined population categorizations from genetic ancestry in the design, analysis, reporting, and interpretation of genetic epidemiology research findings. Finally, we discuss the current state of genomic resources used in genetic association studies, functional interpretation, and clinical and public health translation of genomic findings with respect to diverse populations.

Deciphering signatures of natural selection via deep learning

Identifying genomic regions influenced by natural selection provides fundamental insights into the genetic basis of local adaptation. However, it remains challenging to detect loci under complex spatially varying selection. We propose a deep learning-based framework, DeepGenomeScan, which can detect signatures of spatially varying selection. We demonstrate that DeepGenomeScan outperformed principal component analysis- and redundancy analysis-based genome scans in identifying loci underlying quantitative traits subject to complex spatial patterns of selection. Noticeably, DeepGenomeScan increases statistical power by up to 47.25% under nonlinear environmental selection patterns. We applied DeepGenomeScan to a European human genetic dataset and identified some well-known genes under selection and a substantial number of clinically important genes that were not identified by SPA, iHS, Fst and Bayenv when applied to the same dataset.

Genetic Diversity of CYP3A5 and ABCB1 Variants in East-Central and South European Populations

BACKGROUND

CYP3A5 enzyme encoded by CYP3A5 is important for drug metabolism in gut and liver, whereas P-glycoprotein by ABCB1, is an ATP-dependent drug efflux pump which exports endo- and exogenous substances outside the cell. Aim: The study was to assess the prevalence of CYP3A5 alleles: *1, *2, *3, *4, *6 and *7, and C and T of ABCB1 in Poles, Belarusians and Bosnians and to compare it with the data reported from other European populations. Subjects and methods: Overall, 511 unrelated healthy subjects from Poland (n = 239), Belarus (n = 104) and Bosnia and Herzegovina (n = 168) were included in this study. Allele frequencies and statistical parameters (AMOVA version 2.9.3) were determined. Results: In Poles, Belarusians and Bosnians the *3 allele of CYP3A5 was the most common, and wild-type allele *1, were: 5.8%, 1.6% and 2.1%, respectively. Allele *2 was very rare, and alleles *4, *6 and *7 were not detected. For the populations mentioned above, the ABCB1 allele C was: 48.1%, 51.4%, 52.4%, respectively.

CONCLUSION

In compared populations, the distribution of CYP3A5 variants but not ABCB1, differed significantly. Alleles *4, *6 and *7 of CYP3A5 did not occur or occurred rarely.

Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits

Despite the growing number of genome-wide association studies (GWASs), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWASs are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate, although this is not significant, most likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits.

Various vascular malformations are prevalent in Finnish pseudoxanthoma elasticum (PXE) patients: a national registry study

Background

Pseudoxanthoma elasticum (PXE, OMIM# 264800) is an inborn error of metabolism causing ectopic soft tissue calcification due to low plasma pyrophosphate concentration. We aimed to assess the prevalence of PXE in Finland and to characterize the Finnish PXE population. A nationwide registry search was performed to identify patients with ICD-10 code Q82.84. Information was gathered from available medical records which were requisitioned from hospitals and health centers. Misdiagnosed patients and patients with insufficient records were excluded.

Results

The prevalence of PXE in Finland was 1:260,000 with equal sex distribution. Patients with high conventional cardiovascular risk had more visual and vascular complications than patients with low risk. Four patients (19%) had at least one vascular malformation. A high proportion (33%) of ABCC6 genotypes were of the common homozygous c.3421C > T, p.Arg1141Ter variant. Nine other homozygous or compound heterozygous allelic variants were found.

Conclusions

The prevalence of diagnosed PXE appears to be lower in Finland than in estimates from other countries. Decreased visual acuity is the most prevalent complication. We suggest that various vascular malformations may be an unrecognized feature of PXE.

A deep learning framework for characterization of genotype data

Dimensionality reduction is a data transformation technique widely used in various fields of genomics research. The application of dimensionality reduction to genotype data is known to capture genetic similarity between individuals, and is used for visualization of genetic variation, identification of population structure as well as ancestry mapping. Among frequently used methods are principal component analysis, which is a linear transform that often misses more fine-scale structures, and neighbor-graph based methods which focus on local relationships rather than large-scale patterns. Deep learning models are a type of nonlinear machine learning method in which the features used in data transformation are decided by the model in a data-driven manner, rather than by the researcher, and have been shown to present a promising alternative to traditional statistical methods for various applications in omics research. In this study, we propose a deep learning model based on a convolutional autoencoder architecture for dimensionality reduction of genotype data. Using a highly diverse cohort of human samples, we demonstrate that the model can identify population clusters and provide richer visual information in comparison to principal component analysis, while preserving global geometry to a higher extent than t-SNE and UMAP, yielding results that are comparable to an alternative deep learning approach based on variational autoencoders. We also discuss the use of the methodology for more general characterization of genotype data, showing that it preserves spatial properties in the form of decay of linkage disequilibrium with distance along the genome and demonstrating its use as a genetic clustering method, comparing results to the ADMIXTURE software frequently used in population genetic studies.

SNP characteristics and validation success in genome wide association studies

Genome wide association studies (GWASs) have identified tens of thousands of single nucleotide polymorphisms (SNPs) associated with human diseases and characteristics. A significant fraction of GWAS findings can be false positives. The gold standard for true positives is an independent validation. The goal of this study was to identify SNP features associated with validation success. Summary statistics from the Catalog of Published GWASs were used in the analysis. Since our goal was an analysis of reproducibility, we focused on the diseases/phenotypes targeted by at least 10 GWASs. GWASs were arranged in discovery-validation pairs based on the time of publication, with the discovery GWAS published before validation. We used four definitions of the validation success that differ by stringency. Associations of SNP features with validation success were consistent across the definitions. The strongest predictor of SNP validation was the level of statistical significance in the discovery GWAS. The magnitude of the effect size was associated with validation success in a non-linear manner. SNPs with risk allele frequencies in the range 30-70% showed a higher validation success rate compared to rarer or more common SNPs. Missense, 5'UTR, stop gained, and SNPs located in transcription factor binding sites had a higher validation success rate compared to intergenic, intronic and synonymous SNPs. There was a positive association between validation success and the level of evolutionary conservation of the sites. In addition, validation success was higher when discovery and validation GWASs targeted the same ethnicity. All predictors of validation success remained significant in a multivariate logistic regression model indicating their independent contribution. To conclude, we identified SNP features predicting validation success of GWAS hits. These features can be used to select SNPs for validation and downstream functional studies.

A framework for research into continental ancestry groups of the UK Biobank

BACKGROUND

The UK Biobank is a large prospective cohort, based in the UK, that has deep phenotypic and genomic data on roughly a half a million individuals. Included in this resource are data on approximately 78,000 individuals with "non-white British ancestry." While most epidemiology studies have focused predominantly on populations of European ancestry, there is an opportunity to contribute to the study of health and disease for a broader segment of the population by making use of the UK Biobank's "non-white British ancestry" samples. Here, we present an empirical description of the continental ancestry and population structure among the individuals in this UK Biobank subset.

RESULTS

Reference populations from the 1000 Genomes Project for Africa, Europe, East Asia, and South Asia were used to estimate ancestry for each individual. Those with at least 80% ancestry in one of these four continental ancestry groups were taken forward (N = 62,484). Principal component and K-means clustering analyses were used to identify and characterize population structure within each ancestry group. Of the approximately 78,000 individuals in the UK Biobank that are of "non-white British" ancestry, 50,685, 6653, 2782, and 2364 individuals were associated to the European, African, South Asian, and East Asian continental ancestry groups, respectively. Each continental ancestry group exhibits prominent population structure that is consistent with self-reported country of birth data and geography.

CONCLUSIONS

Methods outlined here provide an avenue to leverage UK Biobank's deeply phenotyped data allowing researchers to maximize its potential in the study of health and disease in individuals of non-white British ancestry.

Fine-scale population structure in five rural populations from the Spanish Eastern Pyrenees using high-coverage whole-genome sequence data

The area of the Spanish Pyrenees is particularly interesting for studying the demographic dynamics of European rural areas given its orography, the main traditional rural condition of its population and the reported higher patterns of consanguinity of the region. Previous genetic studies suggest a gradient of genetic continuity of the area in the West to East axis. However, it has been shown that micro-population substructure can be detected when considering high-quality NGS data and using spatial explicit methods. In this work, we have analyzed the genome of 30 individuals sequenced at 40× from five different valleys in the Spanish Eastern Pyrenees (SEP) separated by less than 140 km along a west to east axis. Using haplotype-based methods and spatial analyses, we have been able to detect micro-population substructure within SEP not seen in previous studies. Linkage disequilibrium and autozygosity analyses suggest that the SEP populations show diverse demographic histories. In agreement with these results, demographic modeling by means of ABC-DL identify heterogeneity in their effective population sizes despite of their close geographic proximity, and suggests that the population substructure within SEP could have appeared around 2500 years ago. Overall, these results suggest that each rural population of the Pyrenees could represent a unique entity.

Safety of alemtuzumab in a nationwide cohort of Finnish multiple sclerosis patients

Background

Alemtuzumab is an effective disease-modifying therapy (DMT) for highly active multiple sclerosis (MS). However, safety concerns limit its use in clinical practice.

Objectives

To evaluate the safety of alemtuzumab in a nationwide cohort of Finnish MS patients.

Methods

In this retrospective case series study, we analyzed the data of all but two MS patients who had received alemtuzumab in Finland until 2019. Data were systematically collected from patient files.

Results

Altogether 121 patients were identified, most of whom had received previous DMTs (82.6%). Median follow-up time after treatment initiation was 30.3 months and exceeded 24 months in 78 patients. Infusion-associated reactions (IARs) were observed in 84.3%, 57.3%, and 57.1% of patients during alemtuzumab courses 1–3, respectively. Serious adverse events (SAEs) were observed in 32.2% of patients, serious IARs in 12.4% of patients, and SAEs other than IARs in 23.1% of patients. Autoimmune adverse events were observed in 30.6% of patients. One patient died of hemophagocytic lymphohistiocytosis, and one patient died of pneumonia. A previously unreported case of thrombotic thrombocytopenic purpura was documented.

Conclusions

SAEs were more frequent in the present cohort than in previous studies. Even though alemtuzumab is a highly effective therapy for MS, vigorous monitoring with a long enough follow-up time is advised.

Admixture Has Shaped Romani Genetic Diversity in Clinically Relevant Variants

Genetic patterns of inter-population variation are a result of different demographic and adaptive histories, which gradually shape the frequency distribution of the variants. However, the study of clinically relevant mutations has a Eurocentric bias. The Romani, the largest transnational minority ethnic group in Europe, originated in South Asia and received extensive gene flow from West Eurasia. Most medical genetic studies have only explored founder mutations related to Mendelian disorders in this population. Here we analyze exome sequences and genome-wide array data of 89 healthy Spanish Roma individuals to study complex traits and disease. We apply a different framework and focus on variants with both increased and decreased allele frequencies, taking into account their local ancestry. We report several OMIM traits enriched for genes with deleterious variants showing increased frequencies in Roma or in non-Roma (e.g., obesity is enriched in Roma, with an associated variant linked to South Asian ancestry; while non-insulin dependent diabetes is enriched in non-Roma Europeans). In addition, previously reported pathogenic variants also show differences among populations, where some variants segregating at low frequency in non-Roma are virtually absent in the Roma. Lastly, we describe frequency changes in drug-response variation, where many of the variants increased in Roma are clinically associated with metabolic and cardiovascular-related drugs. These results suggest that clinically relevant variation in Roma cannot only be characterized in terms of founder mutations. Instead, we observe frequency differences compared to non-Roma: some variants are absent, while other have drifted to higher frequencies. As a result of the admixture events, these clinically damaging variants can be traced back to both European and South Asian-related ancestries. This can be attributed to a different prevalence of some genetic disorders or to the fact that genetic susceptibility variants are mostly studied in populations of European descent, and can differ in individuals with different ancestries.

Genetic history of Calabrian Greeks reveals ancient events and long term isolation in the Aspromonte area of Southern Italy

Calabrian Greeks are an enigmatic population that have preserved and evolved a unique variety of language, Greco, survived in the isolated Aspromonte mountain area of Southern Italy. To understand their genetic ancestry and explore possible effects of geographic and cultural isolation, we genome-wide genotyped a large set of South Italian samples including both communities that still speak Greco nowadays and those that lost the use of this language earlier in time. Comparisons with modern and ancient populations highlighted ancient, long-lasting genetic links with Eastern Mediterranean and Caucasian/Near-Eastern groups as ancestral sources of Southern Italians. Our results suggest that the Aspromonte communities might be interpreted as genetically drifted remnants that departed from such ancient genetic background as a consequence of long-term isolation. Specific patterns of population structuring and higher levels of genetic drift were indeed observed in these populations, reflecting geographic isolation amplified by cultural differences in the groups that still conserve the Greco language. Isolation and drift also affected the current genetic differentiation at specific gene pathways, prompting for future genome-wide association studies aimed at exploring trait-related loci that have drifted up in frequency in these isolated groups.

Functional and clinical implications of genetic structure in 1686 Italian exomes

To reconstruct the phenotypical and clinical implications of the Italian genetic structure, we thoroughly analyzed a whole-exome sequencing data set comprised of 1686 healthy Italian individuals. We found six previously unreported variants with remarkable frequency differences between Northern and Southern Italy in the HERC2, OR52R1, ADH1B, and THBS4 genes. We reported 36 clinically relevant variants (submitted as pathogenic, risk factors, or drug response in ClinVar) with significant frequency differences between Italy and Europe. We then explored putatively pathogenic variants in the Italian exome. On average, our Italian individuals carried 16.6 protein-truncating variants (PTVs), with 2.5% of the population having a PTV in one of the 59 American College of Medical Genetics (ACMG) actionable genes. Lastly, we looked for PTVs that are likely to cause Mendelian diseases. We found four heterozygous PTVs in haploinsufficient genes (KAT6A, PTCH1, and STXBP1) and three homozygous PTVs in genes causing recessive diseases (DPYD, FLG, and PYGM). Comparing frequencies from our data set to other public databases, like gnomAD, we showed the importance of population-specific databases for a more accurate assessment of variant pathogenicity. For this reason, we made aggregated frequencies from our data set publicly available as a tool for both clinicians and researchers (http://nigdb.cineca.it; NIG-ExIT).

Race Based Medicine, Colorblind Disease: How Racism in Medicine Harms Us All

The genome between socially constructed racial groups is 99.5%-99.9% identical; the 0.1%-0.5% variation between any two unrelated individuals is greatest between individuals in the same racial group; and there are no identifiable racial genomic clusters. Nevertheless, race continues to be used as a biological reality in health disparities research, medical guidelines, and standards of care reinforcing the notion that racial and ethnic minorities are inferior, while ignoring the health problems of Whites. This article discusses how the continued misuse of race in medicine and the identification of Whites as the control group, which reinforces this racial hierarchy, are examples of racism in medicine that harm all us. To address this problem, race should only be used as a factor in medicine when explicitly connected to racism or to fulfill diversity and inclusion efforts.

Community-based genetic study of Parkinson's disease in Estonia

OBJECTIVE

To examine the genetic variability of Estonian Parkinson's disease (PD) patients using an ongoing epidemiological study in combination with a genetic analysis.

METHODS

This study was a community-based genetic screening study of 189 PD patients, and 158 age- and sex-matched controls screened for potential mutations in 9 PD genes using next-generation sequencing and multiplex ligation-dependent probe amplification method. Different clinimetric scales and questionnaires were used to examine PD patients and assess clinical characteristics and severity of the disease.

RESULTS

The overall frequency of pathogenic PD-causing variants was 1.1% (2/189), and any rare genetic variant was present in 21.2% (40/189) of the patients and in 8.2% (13/158) of the controls (P < .05). Variants of unknown significance accounted for 10.6% (20/189). Frequency of any GBA variant among PD patients was 10.1% (19/189) and in controls 3.8% (6/158). The frequency of any GBA variant in PD compared to controls was significantly higher (P = .035; OR 2.82; CI 95% 1.05-8.87). Burden of rare variants was not different between patients and controls. Also, a novel GBA pathogenic variant p.E10X was detected.

CONCLUSION

Among different genetic variants identified in Estonian PD patients, GBA variants are the most common, while an overall pathogenic variant frequency was 1.1%.

Global Picture of Genetic Relatedness and the Evolution of Humankind

Simple Summary

The intricacies of human ancestry are buried deep within our DNA. For years, scientists have been working to piece together a vast picture of our genetic lineage. The purpose of this study was to further reveal this global picture of human genetic relatedness using identical-by-descent (IBD) genomic fragments. We processed over 65 million very rare single nucleotide polymorphic (SNP) alleles and detected over 17 million shared IBD fragments, including very short IBD fragments that allowed us to trace common ancestors back to 200,000 years ago. We also determined nine geographical regions representing nine unique genetic components for mankind: East and West Africa, Northern Europe, Arctica, East Asia, Oceania, South Asia, Middle East, and South America. The levels of admixture in every studied population could be assigned to one of these regions and long-term neighboring populations are strikingly similar, despite any political, religious, and cultural differences. Additionally, we observed the topmost admixture to be in central Eurasia. The entire picture of relatedness of all the studied populations presents itself in the form of shared number/size of IBDs, providing novel insights into geographical admixtures and genetic contributions that shaped human ancestry into what it is today.

Abstract

We performed an exhaustive pairwise comparison of whole-genome sequences of 3120 individuals, representing 232 populations from all continents and seven prehistoric people including archaic and modern humans. In order to reveal an intricate picture of worldwide human genetic relatedness, 65 million very rare single nucleotide polymorphic (SNP) alleles have been bioinformatically processed. The number and size of shared identical-by-descent (IBD) genomic fragments for every pair of 3127 individuals have been revealed. Over 17 million shared IBD fragments have been described. Our approach allowed detection of very short IBD fragments (<20 kb) that trace common ancestors who lived up to 200,000 years ago. We detected nine distinct geographical regions within which individuals had strong genetic relatedness, but with negligible relatedness between the populations of these regions. The regions, comprising nine unique genetic components for mankind, are the following: East and West Africa, Northern Europe, Arctica, East Asia, Oceania, South Asia, Middle East, and South America. The level of admixture in every studied population has been apportioned among these nine genetic components. Genetically, long-term neighboring populations are strikingly similar to each other in spite of any political, religious, and cultural differences. The topmost admixture has been observed at the center of Eurasia. These admixed populations (including Uyghurs, Azerbaijanis, Uzbeks, and Iranians) have roughly equal genetic contributions from the Middle East, Europe, China, and India, with additional significant traces from Africa and Arctic. The entire picture of relatedness of all the studied populations unfolds and presents itself in the form of shared number/size of IBDs.

Testing the impact of trait prevalence priors in Bayesian-based genetic prediction modeling of human appearance traits

The prediction of appearance traits by use of solely genetic information has become an established approach and a number of statistical prediction models have already been developed for this purpose. However, given limited knowledge on appearance genetics, currently available models are incomplete and do not include all causal genetic variants as predictors. Therefore such prediction models may benefit from the inclusion of additional information that acts as a proxy for this unknown genetic background. Use of priors, possibly informed by trait category prevalence values in biogeographic ancestry groups, in a Bayesian framework may thus improve the prediction accuracy of previously predicted externally visible characteristics, but has not been investigated as of yet. In this study, we assessed the impact of using trait prevalence-informed priors on the prediction performance in Bayesian models for eye, hair and skin color as well as hair structure and freckles in comparison to the respective prior-free models. Those prior-free models were either similarly defined either very close to the already established ones by using a reduced predictive marker set. However, these differences in the number of the predictive markers should not affect significantly our main outcomes. We observed that such priors often had a strong effect on the prediction performance, but to varying degrees between different traits and also different trait categories, with some categories barely showing an effect. While we found potential for improving the prediction accuracy of many of the appearance trait categories tested by using priors, our analyses also showed that misspecification of those prior values often severely diminished the accuracy compared to the respective prior-free approach. This emphasizes the importance of accurate specification of prevalence-informed priors in Bayesian prediction modeling of appearance traits. However, the existing literature knowledge on spatial prevalence is sparse for most appearance traits, including those investigated here. Due to the limitations in appearance trait prevalence knowledge, our results render the use of trait prevalence-informed priors in DNA-based appearance trait prediction currently infeasible.

The Y Chromosome: A Complex Locus for Genetic Analyses of Complex Human Traits

The Human Y chromosome (ChrY) has been demonstrated to be a powerful tool for phylogenetics, population genetics, genetic genealogy and forensics. However, the importance of ChrY genetic variation in relation to human complex traits is less clear. In this review, we summarise existing evidence about the inherent complexities of ChrY variation and their use in association studies of human complex traits. We present and discuss the specific particularities of ChrY genetic variation, including Y chromosomal haplogroups, that need to be considered in the design and interpretation of genetic epidemiological studies involving ChrY.

Y-Chromosome Genetic Analysis of Modern Polish Population

The study presents a full analysis of the Y-chromosome variability of the modern male Polish population. It is the first study of the Polish population to be conducted with such a large set of data (2,705 individuals), which includes genetic information from inhabitants of all voivodeships, i.e., the first administrative level, in the country and the vast majority of its counties, i.e., the second level. In addition, the available data were divided into clusters corresponding to more natural geographic regions. Genetic analysis included the estimation of F_ST distances, the visualization with the use of multidimensional scaling plots and analysis of molecular variance. Y-chromosome binary haplogroups were classified and visualized with the use of interpolation maps. Results showed that the level of differentiation within Polish population is quite low, but some differences were indicated. It was confirmed that the Polish population is characterized by a high degree of homogeneity, with only slight genetic differences being observed at the regional level. The use of regional clustering as an alternative to counties and voivodeships provided a more detailed view of the genetic structure of the population. Those regional differences identified in the present study highlighted the need for additional division of the population by cultural and ethnic criteria in such studies rather than just by geographical or administrative regionalization.

Principals about principal components in statistical genetics

Principal components (PCs) are widely used in statistics and refer to a relatively small number of uncorrelated variables derived from an initial pool of variables, while explaining as much of the total variance as possible. Also in statistical genetics, principal component analysis (PCA) is a popular technique. To achieve optimal results, a thorough understanding about the different implementations of PCA is required and their impact on study results, compared to alternative approaches. In this review, we focus on the possibilities, limitations and role of PCs in ancestry prediction, genome-wide association studies, rare variants analyses, imputation strategies, meta-analysis and epistasis detection. We also describe several variations of classic PCA that deserve increased attention in statistical genetics applications.

Genomic history of the Italian population recapitulates key evolutionary dynamics of both Continental and Southern Europeans

BACKGROUND

The cline of human genetic diversity observable across Europe is recapitulated at a micro-geographic scale by variation within the Italian population. Besides resulting from extensive gene flow, this might be ascribable also to local adaptations to diverse ecological contexts evolved by people who anciently spread along the Italian Peninsula. Dissecting the evolutionary history of the ancestors of present-day Italians may thus improve the understanding of demographic and biological processes that contributed to shape the gene pool of European populations. However, previous SNP array-based studies failed to investigate the full spectrum of Italian variation, generally neglecting low-frequency genetic variants and examining a limited set of small effect size alleles, which may represent important determinants of population structure and complex adaptive traits. To overcome these issues, we analyzed 38 high-coverage whole-genome sequences representative of population clusters at the opposite ends of the cline of Italian variation, along with a large panel of modern and ancient Euro-Mediterranean genomes.

RESULTS

We provided evidence for the early divergence of Italian groups dating back to the Late Glacial and for Neolithic and distinct Bronze Age migrations having further differentiated their gene pools. We inferred adaptive evolution at insulin-related loci in people from Italian regions with a temperate climate, while possible adaptations to pathogens and ultraviolet radiation were observed in Mediterranean Italians. Some of these adaptive events may also have secondarily modulated population disease or longevity predisposition.

CONCLUSIONS

We disentangled the contribution of multiple migratory and adaptive events in shaping the heterogeneous Italian genomic background, which exemplify population dynamics and gene-environment interactions that played significant roles also in the formation of the Continental and Southern European genomic landscapes.

Mapping co-ancestry connections between the genome of a Medieval individual and modern Europeans

Historical genetic links among similar populations can be difficult to establish. Identity by descent (IBD) analyses find genomic blocks that represent direct genealogical relationships among individuals. However, this method has rarely been applied to ancient genomes because IBD stretches are progressively fragmented by recombination and thus not recognizable after few tens of generations. To explore such genealogical relationships, we estimated long IBD blocks among modern Europeans, generating networks to uncover the genetic structures. We found that Basques, Sardinians, Icelanders and Orcadians form, each of them, highly intraconnected sub-clusters in a European network, indicating dense genealogical links within small, isolated populations. We also exposed individual genealogical links -such as the connection between one Basque and one Icelandic individual- that cannot be uncovered with other, widely used population genetics methods such as PCA or ADMIXTURE. Moreover, using ancient DNA technology we sequenced a Late Medieval individual (Barcelona, Spain) to high genomic coverage and identified IBD blocks shared between her and modern Europeans. The Medieval IBD blocks are statistically overrepresented only in modern Spaniards, which is the geographically closest population. This approach can be used to produce a fine-scale reflection of shared ancestry across different populations of the world, offering a direct genetic link from the past to the present.

Recent Perspectives on Gene-Microbe Interactions Determining Predisposition to Otitis Media

A comprehensive understanding about the pathogenesis of otitis media (OM), one of the most common pediatric diseases, has the potential to alleviate a substantial disease burden across the globe. Advancements in genetic and bioinformatic detection methods, as well as a growing interest in the microbiome, has enhanced the capability of researchers to investigate the interplay between host genes, host microbiome, invading bacteria, and resulting OM susceptibility. Early studies deciphering the role of genetics in OM susceptibility assessed the heritability of the phenotype in twin and triplet studies, followed by linkage studies, candidate gene approaches, and genome-wide association studies that have helped in the identification of specific loci. With the advancements in techniques, various chromosomal regions and genes such as FBXO11, TGIF1, FUT2, FNDC1, and others have been implicated in predisposition to OM, yet questions still remain as to whether these implicated genes truly play a causative role in OM and to what extent. Meanwhile, 16S ribosomal RNA (rRNA) sequencing, microbial quantitative trait loci (mbQTL), and microbial genome-wide association studies (mGWAS) have mapped the microbiome of upper airways sites and therefore helped in enabling a more detailed study of interactions between host polymorphisms and host microbiome composition. Variants of specific genes conferring increased OM susceptibility, such as A2ML1, have also been shown to influence the microbial composition of the outer and middle ear in patients with OM, suggesting their role as mediators of disease. These interactions appear to impact the colonization of known otopathogens (Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis), as well as Neisseria, Gemella, Porphyromonas, Alloprevotella, and Fusobacterium populations that have also been implicated in OM pathogenesis. Meanwhile, studies demonstrating an increased abundance of Dolosigranulum and Corynebacterium in healthy patients compared to those with OM suggest a protective role for these bacteria, thereby introducing potential avenues for future probiotic treatment. Incorporating insights from these genetic, microbiome, and host-pathogen studies will allow for a more robust, comprehensive understanding of OM pathogenesis that can ultimately facilitate in the development of exciting new treatment modalities.

Human mitochondrial DNA lineages in Iron-Age Fennoscandia suggest incipient admixture and eastern introduction of farming-related maternal ancestry

Human ancient DNA studies have revealed high mobility in Europe’s past, and have helped to decode the human history on the Eurasian continent. Northeastern Europe, especially north of the Baltic Sea, however, remains less well understood largely due to the lack of preserved human remains. Finland, with a divergent population history from most of Europe, offers a unique perspective to hunter-gatherer way of life, but thus far genetic information on prehistoric human groups in Finland is nearly absent. Here we report 103 complete ancient mitochondrial genomes from human remains dated to AD 300–1800, and explore mtDNA diversity associated with hunter-gatherers and Neolithic farmers. The results indicate largely unadmixed mtDNA pools of differing ancestries from Iron-Age on, suggesting a rather late genetic shift from hunter-gatherers towards farmers in North-East Europe. Furthermore, the data suggest eastern introduction of farmer-related haplogroups into Finland, contradicting contemporary genetic patterns in Finns.

Candidate Gene and Genome-Wide Association Studies for Circulating Leptin Levels Reveal Population and Sex-Specific Associations in High Cardiovascular Risk Mediterranean Subjects

Leptin is a hormone crucial in the regulation of food intake and body-weight maintenance. However, the genes and gene variants that influence its plasma levels are still not well known. Results of studies investigating polymorphisms in candidate genes have been inconsistent, and, in addition, very few genome-wide association studies (GWAS) have been undertaken. Our aim was to investigate the genes and gene variants most associated with plasma leptin concentrations in a high-cardiovascular-risk Mediterranean population. We measured plasma leptin in 1011 men and women, and analyzed the genetic factors associated using three approaches: (1) Analyzing the single nucleotide polymorphisms (SNPs) reported in a GWAS meta-analysis in other populations (including an SNP in/near each of these LEP, SLC32A1, GCKR, CCNL, COBLL1, and FTO genes); (2) Investigating additional SNPs in/near those genes, also including the RLEP gene; and (3) Undertaking a GWAS to discover new genes. We did not find any statistically significant associations between the previously published SNPs and plasma leptin (Ln) in the whole population adjusting for sex and age. However, on undertaking an extensive screening of other gene variants in those genes to capture a more complete set of SNPs, we found more associations. Outstanding among the findings was the heterogeneity per sex. We detected several statistically significant interaction terms with sex for these SNPs in the candidate genes. The gene most associated with plasma leptin levels was the FTO gene in men (specifically the rs1075440 SNP) and the LEPR in women (specifically the rs12145690 SNP). In the GWAS on the whole population, we found several new associations at the p < 1 × 10^-5 level, among them with the rs245908-CHN2 SNP (p = 1.6 × 10^-6). We also detected a SNP*sex interaction at the GWAS significance level (p < 5 × 10^-8), involving the SLIT3 gene, a gene regulated by estrogens. In conclusion, our study shows that the SNPs selected as relevant for plasma leptin levels in other populations, are not good markers for this Mediterranean population, so supporting those studies claiming a bias when generalizing GWAS results to different populations. These population-specific differences may include not only genetic characteristics, but also age, health status, and the influence of other environmental variables. In addition, we have detected several sex-specific effects. These results suggest that genomic analyses, involving leptin, should be estimated by sex and consider population-specificity for more precise estimations.

Inter-individual genomic heterogeneity within European population isolates

A number of studies carried out since the early ‘70s has investigated the effects of isolation on genetic variation within and among human populations in diverse geographical contexts. However, no extensive analysis has been carried out on the heterogeneity among genomes within isolated populations. This issue is worth exploring since events of recent admixture and/or subdivision could potentially disrupt the genetic homogeneity which is to be expected when isolation is prolonged and constant over time. Here, we analyze literature data relative to 87,815 autosomal single-nucleotide polymorphisms, which were obtained from a total of 28 European populations. Our results challenge the traditional paradigm of population isolates as structured as genetically (and genomically) uniform entities. In fact, focusing on the distribution of variance of intra-population diversity measures across individuals, we show that the inter-individual heterogeneity of isolated populations is at least comparable to the open ones. More in particular, three small and highly inbred isolates (Sappada, Sauris and Timau in Northeastern Italy) were found to be characterized by levels of inter-individual heterogeneity largely exceeding that of all other populations, possibly due to relatively recent events of genetic introgression. Finally, we propose a way to monitor the effects of inter-individual heterogeneity in disease-gene association studies.

Distinct genetic variation and heterogeneity of the Iranian population

Iran, despite its size, geographic location and past cultural influence, has largely been a blind spot for human population genetic studies. With only sparse genetic information on the Iranian population available, we pursued its genome-wide and geographic characterization based on 1021 samples from eleven ethnic groups. We show that Iranians, while close to neighboring populations, present distinct genetic variation consistent with long-standing genetic continuity, harbor high heterogeneity and different levels of consanguinity, fall apart into a cluster of similar groups and several admixed ones and have experienced numerous language adoption events in the past. Our findings render Iran an important source for human genetic variation in Western and Central Asia, will guide adequate study sampling and assist the interpretation of putative disease-implicated genetic variation. Given Iran's internal genetic heterogeneity, future studies will have to consider ethnic affiliations and possible admixture.