The use of genealogy databases for risk assessment in genetic health service: a systematic review

PREDICTION OF HEREDITARY CANCERS USING NEURAL NETWORKS

Family history is a major risk factor for many types of cancer. Mendelian risk prediction models translate family histories into cancer risk predictions, based on knowledge of cancer susceptibility genes. These models are widely used in clinical practice to help identify high-risk individuals. Mendelian models leverage the entire family history, but they rely on many assumptions about cancer susceptibility genes that are either unrealistic or challenging to validate, due to low mutation prevalence. Training more flexible models, such as neural networks, on large databases of pedigrees can potentially lead to accuracy gains. In this paper we develop a framework to apply neural networks to family history data and investigate their ability to learn inherited susceptibility to cancer. While there is an extensive literature on neural networks and their state-of-the-art performance in many tasks, there is little work applying them to family history data. We propose adaptations of fully-connected neural networks and convolutional neural networks to pedigrees. In data simulated under Mendelian inheritance, we demonstrate that our proposed neural network models are able to achieve nearly optimal prediction performance. Moreover, when the observed family history includes misreported cancer diagnoses, neural networks are able to outperform the Mendelian BRCAPRO model embedding the correct inheritance laws. Using a large dataset of over 200,000 family histories, the Risk Service cohort, we train prediction models for future risk of breast cancer. We validate the models using data from the Cancer Genetics Network.

Genomic imprinting analyses identify maternal effects as a cause of phenotypic variability in type 1 diabetes and rheumatoid arthritis

Imprinted genes, giving rise to parent-of-origin effects (POEs), have been hypothesised to affect type 1 diabetes (T1D) and rheumatoid arthritis (RA). However, maternal effects may also play a role. By using a mixed model that is able to simultaneously consider all kinds of POEs, the importance of POEs for the development of T1D and RA was investigated in a variance components analysis. The analysis was based on Swedish population-scale pedigree data. With P = 0.18 (T1D) and P = 0.26 (RA) imprinting variances were not significant. Explaining up to 19.00% (± 2.00%) and 15.00% (± 6.00%) of the phenotypic variance, the maternal environmental variance was significant for T1D (P = 1.60 × 10-24) and for RA (P = 0.02). For the first time, the existence of maternal genetic effects on RA was indicated, contributing up to 16.00% (± 3.00%) of the total variance. Environmental factors such as the social economic index, the number of offspring, birth year as well as their interactions with sex showed large effects.

Mining archival genealogy databases to gain new insights into broader historical issues

Purpose

Several genealogical databases are now publicly available on the Web. The information stored in such databases is not only of interest for genealogical research but might also be used in broader historical studies. As a case study, this paper aims to explore what a crowdsourced genealogical online database can tell about income inequality in Denmark during the First World War.

Design/methodology/approach

The analysis is based on 55,000 family-level records on the payment of local income taxes in a major Danish provincial town (Esbjerg) from a publicly available database on the website of The Esbjerg City Archives combined with official statistics from Statistics Denmark.

Findings

Denmark saw a sharp increase in income inequality during the First World War. The analysis shows that the new riches during the First World War in a harbour city such as Esbjerg were not “goulash barons” or stock-market speculators but fishermen. There were no fishermen in the top 1per cent of the income distribution in 1913. In 1917, more than 37 per cent of the family heads in this part of the income distribution were fishermen.

Originality/value

The paper illustrates how large-scale microdata from publicly available genealogical Web databases might be used to gain new insights into broader historical issues.

Inferring Transmission Histories of Rare Alleles in Population-Scale Genealogies

Learning the transmission history of alleles through a family or population plays an important role in evolutionary, demographic, and medical genetic studies. Most classical models of population genetics have attempted to do so under the assumption that the genealogy of a population is unavailable and that its idiosyncrasies can be described by a small number of parameters describing population size and mate choice dynamics. Large genetic samples have increased sensitivity to such modeling assumptions, and large-scale genealogical datasets become a useful tool to investigate realistic genealogies. However, analyses in such large datasets are often intractable using conventional methods. We present an efficient method to infer transmission paths of rare alleles through population-scale genealogies. Based on backward-time Monte Carlo simulations of genetic inheritance, we use an importance sampling scheme to dramatically speed up convergence. The approach can take advantage of available genotypes of subsets of individuals in the genealogy including haplotype structure as well as information about the mode of inheritance and general prevalence of a mutation or disease in the population. Using a high-quality genealogical dataset of more than three million married individuals in the Quebec founder population, we apply the method to reconstruct the transmission history of chronic atrial and intestinal dysrhythmia (CAID), a rare recessive disease. We identify the most likely early carriers of the mutation and geographically map the expected carrier rate in the present-day French-Canadian population of Quebec.

Electronically ascertained extended pedigrees in breast cancer genetic counseling

A comprehensive pedigree, usually provided by the counselee and verified by medical records, is essential for risk assessment in cancer genetic counseling. Collecting the relevant information is time-consuming and sometimes impossible. We studied the use of electronically ascertained pedigrees (EGP). The study group comprised women (n = 1352) receiving HBOC genetic counseling between December 2006 and December 2016 at Landspitali in Iceland. EGP's were ascertained using information from the population-based Genealogy Database and Icelandic Cancer Registry. The likelihood of being positive for the Icelandic founder BRCA2 pathogenic variant NM_000059.3:c.767_771delCAAAT was calculated using the risk assessment program Boadicea. We used this unique data to estimate the optimal size of pedigrees, e.g., those that best balance the accuracy of risk assessment using Boadicea and cost of ascertainment. Sub-groups of randomly selected 104 positive and 105 negative women for the founder BRCA2 PV were formed and Receiver Operating Characteristics curves compared for efficiency of PV prediction with a Boadicea score. The optimal pedigree size included 3° relatives or up to five generations with an average no. of 53.8 individuals (range 9-220) (AUC 0.801). Adding 4° relatives did not improve the outcome. Pedigrees including 3° relatives are difficult and sometimes impossible to generate with conventional methods. Pedigrees ascertained with data from pre-existing genealogy databases and cancer registries can save effort and contain more information than traditional pedigrees. Genetic services should consider generating EGP's which requires access to an accurate genealogy database and cancer registry. Local data protection laws and regulations have to be addressed.

Quantitative analysis of population-scale family trees with millions of relatives

Family trees have vast applications in fields as diverse as genetics, anthropology, and economics. However, the collection of extended family trees is tedious and usually relies on resources with limited geographical scope and complex data usage restrictions. We collected 86 million profiles from publicly available online data shared by genealogy enthusiasts. After extensive cleaning and validation, we obtained population-scale family trees, including a single pedigree of 13 million individuals. We leveraged the data to partition the genetic architecture of human longevity and to provide insights into the geographical dispersion of families. We also report a simple digital procedure to overlay other data sets with our resource.

Counsellee's experience of cancer genetic counselling with pedigrees that automatically incorporate genealogical and cancer database information

While pedigree drawing software is often utilised in genetic services, the use of genealogical databases in genetic counselling is unusual. This is mainly because of the unavailability of such databases in most countries. Electronically generated pedigrees used for cancer genetic counselling in Iceland create pedigrees that automatically incorporate information from a large, comprehensive genealogy database and nation-wide cancer registry. The aim of this descriptive qualitative study was to explore counsellees' experiences of genetic services, including family history taking, using these electronically generated pedigrees. Four online focus groups with 19 participants were formed, using an asynchronous posting method. Participants were encouraged to discuss their responses to questions posted on the website by the researcher. The main themes arising were motivation, information and trust, impact of testing and emotional responses. Most of the participants expressed trust in the method of using electronically generated pedigrees, although some voiced worries about information safety. Many experienced worry and anxiety while waiting for results of genetic testing, but limited survival guilt was noted. Family communication was either unchanged or improved following genetic counselling. The use of electronically generated pedigrees was well received by participants, and they trusted the information obtained via the databases. Age did not seem to influence responses. These results may be indicative of the particular culture in Iceland, where genealogical information is well known and freely shared. Further studies are needed to determine whether use of similar approaches to genealogical information gathering may be acceptable elsewhere.

Iceland-genetic counseling services

This brief report aims to give an overview of the history and current status of clinical genetics services in Iceland and specific genetic counseling considerations for Iceland's population. Presently, there are two part time medical geneticists and one full time genetic counselor with an MSc education from Cardiff, within the Department of Genetic and Molecular Medicine, based in Iceland's only tertiary healthcare facility, Landspitali, the National University Hospital. An oncologist (20 %) also contributes to the cancer genetic counseling service. In addition, a pediatric medical geneticist has a 25 % appointment at the Children's Hospital. No other health care organization offers genetic counseling, and there are no private genetic counseling services.