Whole-exome sequencing data of suicide victims who had suffered from major depressive disorder

Tracing genetic connections of ancient Hungarians to the 6th-14th century populations of the Volga-Ural region

Most of the early Hungarian tribes originated from the Volga-Kama and South-Ural regions, where they were composed of a mixed population based on historical, philological and archaeological data. We present here the uniparental genetic makeup of the mediaeval era of these regions that served as a melting pot for ethnic groups with different linguistic and historical backgrounds. Representing diverse cultural contexts, the new genetic data originate from ancient proto-Ob-Ugric people from Western Siberia (6th-13th century), the pre-Conquest period and subsisting Hungarians from the Volga-Ural region (6th-14th century) and their neighbours. By examining the eastern archaeology traits of Hungarian prehistory, we also study their genetic composition and origin in an interdisciplinary framework. We analyzed 110 deep-sequenced mitogenomes and 42 Y-chromosome haplotypes from 18 archaeological sites in Russia. The results support the studied groups' genetic relationships regardless of geographical distances, suggesting large-scale mobility. We detected long-lasting genetic connections between the sites representing the Kushnarenkovo and Chiyalik cultures and the Carpathian Basin Hungarians and confirmed the Uralic transmission of several East Eurasian uniparental lineages in their gene pool. Based on phylogenetics, we demonstrate and model the connections and splits of the studied Volga-Ural and conqueror groups. Early Hungarians and their alliances conquered the Carpathian Basin around 890 AD. Re-analysis of the Hungarian conquerors' maternal gene pool reveals numerous surviving maternal relationships in both sexes; therefore, we conclude that men and women came to the Carpathian Basin together, and although they were subsequently genetically fused into the local population, certain eastern lineages survived for centuries.

'Omics' of suicidal behaviour: A path to personalised psychiatry

Psychiatric disorders, including suicide, are complex disorders that are affected by many different risk factors. It has been estimated that genetic factors contribute up to 50% to suicide risk. As the candidate gene approach has not identified a gene or set of genes that can be defined as biomarkers for suicidal behaviour, much is expected from cutting edge technological approaches that can interrogate several hundred, or even millions, of biomarkers at a time. These include the '-omic' approaches, such as genomics, transcriptomics, epigenomics, proteomics and metabolomics. Indeed, these have revealed new candidate biomarkers associated with suicidal behaviour. The most interesting of these have been implicated in inflammation and immune responses, which have been revealed through different study approaches, from genome-wide single nucleotide studies and the micro-RNA transcriptome, to the proteome and metabolome. However, the massive amounts of data that are generated by the '-omic' technologies demand the use of powerful computational analysis, and also specifically trained personnel. In this regard, machine learning approaches are beginning to pave the way towards personalized psychiatry.

Common and Unique Genetic Background between Attention-Deficit/Hyperactivity Disorder and Excessive Body Weight

Comorbidity studies show that children with ADHD have a higher risk of being overweight and obese than healthy children. This study aimed to assess the genetic alternations that differ between and are shared by ADHD and excessive body weight (EBW). The sample consisted of 743 Polish children aged between 6 and 17 years. We analyzed a unique set of genes and polymorphisms selected for ADHD and/or obesity based on gene prioritization tools. Polymorphisms in the KCNIP1, SLC1A3, MTHFR, ADRA2A, and SLC6A2 genes proved to be associated with the risk of ADHD in the studied population. The COMT gene polymorphism was one that specifically increased the risk of EBW in the ADHD group. Using the whole-exome sequencing technique, we have shown that the ADHD group contains rare and protein-truncating variants in the FBXL17, DBH, MTHFR, PCDH7, RSPH3, SPTBN1, and TNRC6C genes. In turn, variants in the ADRA2A, DYNC1H1, MAP1A, SEMA6D, and ZNF536 genes were specific for ADHD with EBW. In this way, we confirmed, at the molecular level, the existence of genes specifically predisposing to EBW in ADHD patients, which are associated with the biological pathways involved in the regulation of the reward system, intestinal microbiome, and muscle metabolism.