Origins of human genetics. A personal perspective

Genetics evolved as a field of science after 1900 with new theories being derived from experiments obtained in fruit flies, bacteria, and viruses. This personal account suggests that the origins of human genetics can best be traced to the years 1949 to 1959. Several genetic scientific advances in genetics in 1949 yielded results directly relating to humans for the first time, except for a few earlier observations. In 1949 the first textbook of human genetics was published, the American Journal of Human Genetics was founded, and in the previous year the American Society of Human Genetics. In 1940 in Britain a textbook entitled Introduction to Medical Genetics served as a foundation for introducing genetic aspects into medicine. The introduction of new methods for analyzing chromosomes and new biochemical assays using cultured cells in 1959 and subsequent years revealed that many human diseases, including cancer, have genetic causes. It became possible to arrive at a precise cause-related genetic diagnosis. As a result the risk of occurrence or re-occurrence of a disease within a family could be assessed correctly. Genetic counseling as a new concept became a basis for improved patient care. Taken together the advances in medically orientated genetic research and patient care since 1949 have resulted in human genetics being both, a basic medical and a basic biological science. Prior to 1949 genetics was not generally viewed in a medical context. Although monogenic human diseases were recognized in 1902, their occurrence and distribution were considered mainly at the population level.

Going wild for functional genomics: RNA interference as a tool to study gene-behavior associations in diverse species and ecological contexts

Identifying the genetic basis of behavior has remained a challenge for biologists. A major obstacle to this goal is the difficulty of examining gene function in an ecologically relevant context. New tools such as CRISPR/Cas9, which alter the germline of an organism, have taken center stage in functional genomics in non-model organisms. However, germline modifications of this nature cannot be ethically implemented in the wild as a part of field experiments. This impediment is more than technical. Gene function is intimately tied to the environment in which the gene is expressed, especially for behavior. Most lab-based studies fail to recapitulate an organism's ecological niche, thus most published functional genomics studies of gene-behavior relationships may provide an incomplete or even inaccurate assessment of gene function. In this review, we highlight RNA interference as an especially effective experimental method to deepen our understanding of the interplay between genes, behavior, and the environment. We highlight the utility of RNAi for researchers investigating behavioral genetics, noting unique attributes of RNAi including transience of effect and the feasibility of releasing treated animals into the wild, that make it especially useful for studying the function of behavior-related genes. Furthermore, we provide guidelines for planning and executing an RNAi experiment to study behavior, including challenges to consider. We urge behavioral ecologists and functional genomicists to adopt a more fully integrated approach which we call "ethological genomics". We advocate this approach, utilizing tools such as RNAi, to study gene-behavior relationships in their natural context, arguing that such studies can provide a deeper understanding of how genes can influence behavior, as well as ecological aspects beyond the organism that houses them.

Genetic causes of PD: A pathway to disease modification

The underline neuropathology of Parkinson disease is pleiomorphic and its genetic background diverse. Possibly because of this heterogeneity, no effective disease modifying therapy is available. In this paper we give an overview of the genetics of Parkinson disease and explain how this is relevant for the development of new therapies. This article is part of the special issue entitled 'The Quest for Disease-Modifying Therapies for Neurodegenerative Disorders'.

An overview of 20 years of genetic studies in pheochromocytoma and paraganglioma

Paragangliomas and pheochromocytomas (PPGL) are rare neuroendocrine tumours characterized by a strong genetic determinism. Over the past 20 years, evolution of PPGL genetics has revealed that around 40% of PPGL are genetically determined, secondary to a germline mutation in one of more than twenty susceptibility genes reported so far. More than half of the mutations occur in one of the SDHx genes (SDHA, SDHB, SDHC, SDHD, SDHAF2), which encode the different subunits and assembly protein of a mitochondrial enzyme, succinate dehydrogenase. These susceptibility genes predispose to early forms (VHL, RET, SDHD, EPAS1, DLST), syndromic (RET, VHL, EPAS1, NF1, FH), multiple (SDHD, TMEM127, MAX, DLST, MDH2, GOT2) or malignant (SDHB, FH, SLC25A11) PPGL. The discovery of a germline mutation in one of these genes changes the patient's follow-up and allows genetic screening of affected families and the presymptomatic follow-up of relatives carrying a mutation.

Cushing syndrome: Old and new genes

Cushing syndrome (CS) describes the signs and symptoms caused by exogenous or endogenous hypercortisolemia. Endogenous CS is caused by either ACTH-dependent sources (pituitary or ectopic) or ACTH-independent (adrenal) hypercortisolemia. Several genes are currently known to contribute to the pathogenesis of CS. Germline gene defects, such as MEN1, AIP, PRKAR1A and others, often present in patients with pituitary or adrenal involvement as part of a genetic syndrome. Somatic defects in genes, such as USP8, TP53, and others, are also involved in the development of pituitary or adrenal tumors in a large percentage of patients with CS, and give insight in pathways involved in pituitary or adrenal tumorigenesis.

Old and new genes in primary aldosteronism

Primary aldosteronism (PA) is the most common form of secondary hypertension affecting 5%-10% of patients with arterial hypertension. In PA, high blood pressure is associated with high aldosterone and low renin levels, and often hypokalemia. In a majority of cases, autonomous aldosterone production by the adrenal gland is caused by an aldosterone producing adenoma (APA) or bilateral adrenal hyperplasia (BAH). During the last ten years, a better knowledge of the pathophysiology of PA came from the discovery of somatic and germline mutations in different genes in both sporadic and familial forms of the disease. Those genes code for ion channels and pumps, as well as proteins involved in adrenal cortex development and function. Targeted next generation sequencing following immunohistochemistry guided detection of aldosterone synthase expression allows detection of somatic mutations in up to 90% of APA, while whole exome sequencing has discovered the genetic causes of four different familial forms of PA. The identification, in BAH, of somatic mutations in aldosterone producing cell clusters open new perspectives in our understanding of the bilateral form of the disease and the development of new therapeutic approaches.

Global Genetic Networks and the Genotype-to-Phenotype Relationship

Genetic interactions identify combinations of genetic variants that impinge on phenotype. With whole-genome sequence information available for thousands of individuals within a species, a major outstanding issue concerns the interpretation of allelic combinations of genes underlying inherited traits. In this Review, we discuss how large-scale analyses in model systems have illuminated the general principles and phenotypic impact of genetic interactions. We focus on studies in budding yeast, including the mapping of a global genetic network. We emphasize how information gained from work in yeast translates to other systems, and how a global genetic network not only annotates gene function but also provides new insights into the genotype-to-phenotype relationship.

Advances in Knowledge of Candidate Genes Acting at the Beta-Cell Level in the Pathogenesis of T1DM

T1DM (type 1 diabetes mellitus), which results from the irreversible elimination of beta-cells mediated by autoreactive T cells, is defined as an autoimmune disease. It is widely accepted that T1DM is caused by a combination of genetic and environmental factors, but the precise underlying molecular mechanisms are still unknown. To date, more than 50 genetic risk regions contributing to the pathogenesis of T1DM have been identified by GWAS (genome-wide association studies). Notably, more than 60% of the identified candidate genes are expressed in islets and beta-cells, which makes it plausible that these genes act at the beta-cell level and play a key role in the pathogenesis of T1DM. In this review, we focus on the current status of candidate genes that act at the beta-cell level by regulating the innate immune response and antiviral activity, affecting susceptibility to proapoptotic stimuli and influencing the pancreatic beta-cell phenotype.

Werner syndrome (WRN) gene variants and their association with altered function and age-associated diseases

Werner syndrome (WS) is a heritable autosomal recessive human disorder characterized by the premature onset of several age-associated pathologies including cancer. The protein defective in WS patients, WRN, is encoded by a member of the human RECQ gene family that contains both a DNA exonuclease and a helicase domain. WRN has been shown to participate in several DNA metabolic pathways including DNA replication, recombination and repair, as well as telomere maintenance and transcription modulation. Here we review base pair-level genetic variation that has been documented in WRN, with an emphasis on non-synonymous coding single nucleotide polymorphisms (SNPs) and their associations with anthropomorphic features, longevity and disease risk. These associations have been challenging to identify, as many reported WRN SNP associations appear to be further conditioned upon ethnic, age, gender or other environmental co-variables. The WRN variant phenotypic associations identified to date are intriguing, and several are of clear clinical import. Consequently, it will be important to extend these initial associations and to identify the mechanisms and conditions under which specific WRN variants may compromise WRN function to drive cellular and organismal phenotypes as well as disease risk.

Genetics of non-syndromic childhood obesity and the use of high-throughput DNA sequencing technologies

BACKGROUND

Childhood obesity is a serious public health problem associated with the development of several chronic diseases, such as type 2 diabetes mellitus, dyslipidemia, and hypertension. The elevated prevalence of obesity is mostly due to inadequate diet and lifestyle, but it is also influenced by genetic factors.

OBJECTIVES

To review recent advances in the field of the genetics of obesity. We summarize the list of genes associated with the rare non-syndromic forms of obesity, and explain their function. Furthermore, we discuss the technologies that are available for the genetic diagnosis of obesity.

RESULTS

Several studies reported that single gene variants cause Mendelian forms of obesity, determined by mutations of major effect in single genes. Rare, non-syndromic forms of obesity are a result of loss-of-function mutations in genes that act on the development and function of the hypothalamus or the leptin-melanocortin pathway. These variants disrupt enzymes and receptors that play a role in energy homeostasis, resulting in severe early-onset obesity and endocrine dysfunctions. Different approaches and technologies have been used to understand the genetic background of obesity. Currently, whole genome and whole exome sequencing are important diagnostic tools to identify new genes and variants associated with severe obesity, but other approaches are also useful at individual or population levels, such as linkage analysis, candidate gene sequencing, chromosomal microarray analysis, and genome-wide association studies.

CONCLUSIONS

The understanding of the genetic causes of obesity and the usefulness and limitations of the genetic diagnostic approaches can contribute to the development of new personalized therapeutic targets against obesity.

New Genes Causing Hereditary Parkinson's Disease or Parkinsonism

PURPOSE OF REVIEW

This article reviews was to review genes where putative or confirmed pathogenic mutations causing Parkinson's disease or Parkinsonism have been identified since 2012, and summarizes the clinical and pathological picture of the associated disease subtypes.

RECENT FINDINGS

Newly reported genes for dominant Parkinson's disease are DNAJC13, CHCHD2, and TMEM230. However, the evidence for a disease-causing role is not conclusive, and further genetic and functional studies are warranted. RIC3 mutations have been reported from one family but not yet encountered in other patients. New genes for autosomal recessive disease include SYNJ1, DNAJC6, VPS13C, and PTRHD1. Deletions of a region on chromosome 22 (22q11.2del) are also associated with early-onset PD, but the mode of inheritance and the underlying causative gene remain unclear. PODXL mutations were reported in autosomal recessive PD, but their roles remain to be confirmed. Mutations in RAB39B cause an X-linked Parkinsonian disorder. Mutations in the new dominant PD genes have generally been found in medium- to late-onset Parkinson's disease. Many mutations in the new recessive and X-chromosomal genes cause severe atypical juvenile Parkinsonism, but less devastating mutations in these genes may cause PD.

Lessons from the genomes and transcriptomes of filarial nematodes

Human filarial infections are a leading cause of morbidity in the developing world. While a small arsenal of drugs exists to treat these infections, there remains a tremendous need for the development of additional interventions. Recent genome sequences and transcriptome analyses of filarial nematodes have provided novel biological insight and allowed for the prediction of novel drug targets as well as potential vaccine candidates. In this review, we discuss the currently available data, insights gained into the metabolism of these organisms, and how the filaria field can move forward by leveraging these data.

Genetic markers: Potential candidates for cardiovascular disease

The effective prevention of cardiovascular disease depends upon the ability to recognize the high-risk individuals at an early stage of the disease or long before the development of adverse events. Evolving technologies in the fields of proteomics, metabolomics, and genomics have played a significant role in the discovery of cardiovascular biomarkers, but so far these methods have achieved the modest success. Hence, there is a crucial need for more reliable, suitable, and lasting diagnostic and therapeutic markers to screen the disease well in time to start the clinical aid to the patients. Gene polymorphisms associated with the cardiovascular disease play a decisive role in the disease onset. Therefore, the genetic marker evaluation to classify high-risk patients from low-risk patients trends an effective approach to patient management and care. Currently, there are no genetic markers available for extensive adoption as risk factors for coronary vascular disease, yet, there are numerous promising, biologically acceptable candidates. Many of these gene biomarkers, alone or in combination, can play an essential role in the prediction of cardiovascular risk. The present review highlights some putative emerging genetic biomarkers that could facilitate more authentic and fast diagnosis of CVD. This review also briefly describes few technological approaches employed in the biomarker search.

Osteosarcoma Genetics and Epigenetics: Emerging Biology and Candidate Therapies

Osteosarcoma is the most common primary malignancy of bone, typically presenting in the first or second decade of life. Unfortunately, clinical outcomes for osteosarcoma patients have not substantially improved in over 30 years. This stagnation in therapeutic advances is perhaps explained by the genetic, epigenetic, and biological complexities of this rare tumor. In this review we provide a general background on the biology of osteosarcoma and the clinical status quo. We go on to enumerate the genetic and epigenetic defects identified in osteosarcoma. Finally, we discuss ongoing large-scale studies in the field and potential new therapies that are currently under investigation.

From integrative genomics to therapeutic targets

Combinatorial approaches that integrate conventional pathology with genomic profiling and functional genomics have begun to enhance our understanding of the genetic basis of breast cancer. These methods have identified key genotypic-phenotypic correlations in different breast cancer subtypes that have led to the discovery of genetic dependencies that drive their behavior. Moreover, this knowledge has been applied to define novel tailored therapies for these groups of patients with cancer. With the current emphasis on characterizing the mutational repertoire of breast cancers by next-generation sequencing, the question remains as to what constitutes a driver event. By focusing efforts on homogenous subgroups of breast cancer and integrating orthogonal data-types combined with functional approaches, we can begin to unravel the heterogeneity and identify aberrations that can be therapeutically targeted.

Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype-phenotype relationships and its relevance to crop improvement

More accurate and precise phenotyping strategies are necessary to empower high-resolution linkage mapping and genome-wide association studies and for training genomic selection models in plant improvement. Within this framework, the objective of modern phenotyping is to increase the accuracy, precision and throughput of phenotypic estimation at all levels of biological organization while reducing costs and minimizing labor through automation, remote sensing, improved data integration and experimental design. Much like the efforts to optimize genotyping during the 1980s and 1990s, designing effective phenotyping initiatives today requires multi-faceted collaborations between biologists, computer scientists, statisticians and engineers. Robust phenotyping systems are needed to characterize the full suite of genetic factors that contribute to quantitative phenotypic variation across cells, organs and tissues, developmental stages, years, environments, species and research programs. Next-generation phenotyping generates significantly more data than previously and requires novel data management, access and storage systems, increased use of ontologies to facilitate data integration, and new statistical tools for enhancing experimental design and extracting biologically meaningful signal from environmental and experimental noise. To ensure relevance, the implementation of efficient and informative phenotyping experiments also requires familiarity with diverse germplasm resources, population structures, and target populations of environments. Today, phenotyping is quickly emerging as the major operational bottleneck limiting the power of genetic analysis and genomic prediction. The challenge for the next generation of quantitative geneticists and plant breeders is not only to understand the genetic basis of complex trait variation, but also to use that knowledge to efficiently synthesize twenty-first century crop varieties.

Future directions in vitamin D and cardiovascular research

AIMS

Evidence is accumulating that vitamin D status may influence the risk of cardiovascular disease (CVD). Final confirmation for a causal relationship between vitamin D and CVD is however still lacking. The present viewpoint article outlines several future research directions to close this gap.

DATA SYNTHESIS

Future directions include the need of performing large randomised controlled supplementation trials with vitamin D in specific risk groups. In addition, large register sets of data on vitamin D supplementation can be used, provided that adequate statistical methods such as propensity score modelled analysis are applied. To better understand vitamin D-mediated effects on CVD risk, the routine measurement of circulating levels of the hormonal vitamin D form, 1,25-dihydroxyvitamin D, is also necessary, in addition to the determination of its precursor 25-hydroxyvitamin D. Further, genetic association studies may help in clarifying the contribution of vitamin D to the development of CVD. Finally, the interrelationship of vitamin D with physical activity should be considered when studying CVD risk.

CONCLUSIONS

Overall, it can be expected that the next 10-15 years will provide an increased clarity concerning the role of vitamin D in CVD.

Robust replication of genotype-phenotype associations across multiple diseases in an electronic medical record

Large-scale DNA databanks linked to electronic medical record (EMR) systems have been proposed as an approach for rapidly generating large, diverse cohorts for discovery and replication of genotype-phenotype associations. However, the extent to which such resources are capable of delivering on this promise is unknown. We studied whether an EMR-linked DNA biorepository can be used to detect known genotype-phenotype associations for five diseases. Twenty-one SNPs previously implicated as common variants predisposing to atrial fibrillation, Crohn disease, multiple sclerosis, rheumatoid arthritis, or type 2 diabetes were successfully genotyped in 9483 samples accrued over 4 mo into BioVU, the Vanderbilt University Medical Center DNA biobank. Previously reported odds ratios (OR(PR)) ranged from 1.14 to 2.36. For each phenotype, natural language processing techniques and billing-code queries were used to identify cases (n = 70-698) and controls (n = 808-3818) from deidentified health records. Each of the 21 tests of association yielded point estimates in the expected direction. Previous genotype-phenotype associations were replicated (p < 0.05) in 8/14 cases when the OR(PR) was > 1.25, and in 0/7 with lower OR(PR). Statistically significant associations were detected in all analyses that were adequately powered. In each of the five diseases studied, at least one previously reported association was replicated. These data demonstrate that phenotypes representing clinical diagnoses can be extracted from EMR systems, and they support the use of DNA resources coupled to EMR systems as tools for rapid generation of large data sets required for replication of associations found in research cohorts and for discovery in genome science.

The quality of meta-analyses of genetic association studies: a review with recommendations

Although there has been a rapid rise in the publication of meta-analyses of genetic association studies, little is known about their methodological quality. The authors reviewed the quality of 120 randomly selected genetic meta-analyses published between 2005 and 2007. Data extracted included issues of general relevance and other issues specific to genetic epidemiology. Quality was markedly poorer in the 26% of the meta-analyses that accompanied a report on a primary study. Such meta-analyses were predominantly published in specialist journals, and their quality was positively associated with the impact factor of the journal. Among the meta-analyses that did not accompany a primary study, Human Genome Epidemiology reviews tended to score better than the others, although the comparison was limited by relatively small numbers. Comparison of the overall quality with that of genetic meta-analyses published before 2000 showed improvement in both conduct and reporting. However, the quality of the handling of specific genetic issues remains disappointingly low. For a few key general quality issues, the authors compared their findings with findings in other fields of medicine and found that general quality was similar. On the basis of this review, the authors provide practical recommendations for the conduct and reporting of genetic meta-analyses.