Blood cell concentrations for most cell types are highly heritable. Data from Nick Martin’s twin registry provided much of the data for the early heritability and linkage studies of blood cell related traits and have contributed significantly to more recent genomewide association studies that have successfully identified individual genetic loci.

This letter reflects on my collaborations with Nick Martin over the past 18 years. Working together we have applied twin-family and statistical genetics methods to examine the genetic architecture and identify genetic variants influencing a range of physical, psychological and social traits. The common thread across much of this work has been the empirical questions: Why are we the way we are and how can this knowledge help us when things go wrong?

Twins, data and emails. Some of the words that first come to mind when I think of Nick. Lots of twins. With lots of data. And short single-finger-typed emails. And great wine. Well, it works, there is no doubt. That’s how I ended up in Australia, working on asthma genetics.

Recounts how our collaboration with Nick Martin was shaped over two decades, leading to the first studies of predictions from the ‘Dual Route Cascaded’ computational model of reading in twins, and extending into the molecular work, first linkage, fine mapping of genes identified in pedigree studies, into now the genomewide association study era and the first polygenic risk scores for reading and their potential in early clarifying causality and validating interventions, as well as for future global collaborations in improving these predictors and identifying causal variants. We highlight Nick’s warm, future-focused optimism, support and inclusive approach without which none of this would have been possible. The circle of Nick asking, over half a century ago, ‘What genes do you think make some kids get better grades?’ has built a diverse scientific legacy involving thousands of papers and collaborations. The (heritable) traits of curiosity, boldness, warmth, interest in societally important questions, openness to new methods, ambition and collaborative skill to bring into being the infrastructure and samples needed for this research are rare, and we are grateful.

Mapping genetic risk factors for endometriosis continues from early studies on women’s health initiated by Nick Martin and Susan Treloar. Their initial recruitment of endometriosis cases and family members received a major boost and became a flagship project within the Cooperative Research Centre (CRC) for the Discovery of Common Human Disease. We extended the study through a formal collaboration with Professor Stephen Kennedy and his group in Oxford. Our first joint scientific meeting was held in Brisbane and was sadly memorable as the day the planes were flown into the Twin Towers in New York. Our initial collaboration expanded into the International Endometriosis Genetics Consortium (IEGC). The IEGC now has 15 groups around the world, and the most recent meta-analysis will be published this year.

This note reflects on my collaborations with Nick Martin and the GenEpi group over the past 20 years. Over the past two decades, our work together has focused on gene mapping and understanding the genetic architecture of a wide range of traits with particular foci on migraine and common baldness. Our migraine research has included latent class and twin analyses cumulating in genome-wide association analyses which had identified 44 (34 new) risk variants for migraine. Leveraging these results through polygenic risk score analyses identified subgroups of patients likely to respond to triptans (an acute migraine drug), providing the first step toward precision medicine in migraine [Kogelman et al. (2019) Neurology Genetics, 5, e364].

The classical twin design relies on a number of strong number of assumptions in order to yield unbiased estimates of heritability. This includes the equal environments assumption — that monozygotic and dizygotic twins experience similar degrees of environmental similarity — an assumption that is likely to be violated in practice for many traits of interest. An alternative method of estimating heritability that does not suffer from many of these limitations is to model trait similarity between sibling pairs as a function of their empirical genome-wide identity by descent sharing, estimated from genetic markers. In this review, I recount the story behind Nick Martin’s and my development of this method, our first attempts at applying it in a human population and more recent studies using the original and related methods to estimate trait heritability.

Nick Martin is a pioneer in recognizing the need for large sample size to study the complex, heterogeneous and polygenic disorders of common mental disorders. In the predigital era, questionnaires were mailed to thousands of twin pairs around Australia. Always quick to adopt new technology, Nick’s studies progressed to phone interviews and then online. Moreover, Nick was early to recognize the value of collecting DNA samples. As genotyping technologies improved over the years, these twin and family cohorts were used for linkage, candidate gene and genome-wide association studies. These cohorts have underpinned many analyses to disentangle the complex web of genetic and lifestyle factors associated with mental health. With characteristic foresight, Nick is chief investigator of our Australian Genetics of Depression Study, which has recruited 16,000 people with self-reported depression (plus DNA samples) over a time frame of a few months — analyses are currently ongoing. The mantra of sample size, sample size, sample size has guided Nick’s research over the last 30 years and continues to do so.

Nick Martin has had an outsized influence on the field of behavioral genetics. Much of this influence stems from his mentorship of young scientists. I describe Nick’s mentorship, and what makes it special, from a personal perspective.

Cohort studies are essential for conducting large studies of multiple exposures and outcomes in humans. Recently, the ability to combine data from multiple cohorts in, for example, meta-analyses, and the willingness in the genetics community to collaborate to enable replication studies has led to many new insights into the genetic and environmental determinants of human health and behaviors. The contribution of Professor Nicholas Martin to the development of cohort studies, particularly of twin and twin-family studies, over a period of several decades is reviewed. He has contributed to the development and use of both Australian and international resources. The contributions of Australian twin studies to genomewide association projects are multiple, and across multiple domains, from biomarkers, lifestyle and behavior to disorders and disease.

Genetic research into human sexuality was scarce at the end of last century. In 1992 Nick developed a 12-page questionnaire to send to twins to investigate the underpinnings of sexuality. The questionnaire included items about sexual orientation, sociosexuality and sexual behavior, and was completed by almost 5000 twins. The resulting data, unique at the time, has been used to investigate many previously unexaminable research questions. Here we describe how Nick’s questionnaire contributed to our understanding of human sexuality and how we got involved in this endeavor.

I write this commentary as a part of a special issue published in this journal to celebrate Nick Martin’s contribution to the field of human genetics. In this commentary, I briefly describe the background of the Yang et al. (2010) study and show some of the unpublished details of this study, its contribution to tackling the missing heritability problem and Nick’s contribution to the work.

Nicholas Martin’s contribution to science is well known. This article reviews one small part of his pioneering work that integrated political and social attitudes with behavior genetics. Nick Martin, in part, led to a paradigm shift in the social sciences, and in political science in particular. These fields were previously wed to behavioralist approaches and now routinely include genetic influences in both theoretical and empirical study. This article also celebrates a part of Nick’s contribution that many do not know. Nick Martin does not just build science, he builds scientists. There are many who would not be academics or scholars without Nick’s guidance, mentorship and friendship. This review was written to express the deepest appreciation for what he has done and continues to do for science and the scientist.

This paper is about Nick’s contribution to the field of taste genetics, how I became involved and how a study on the genetic association between the perception of sweetness and bitterness ended up examining the influence of intelligence on taste perception.

Professor Nicholas (Nick) Martin spearheaded initial investigations into the genetic basis of political attitudes and behaviors, demonstrating that behaviors that are perceived as socially constructed could have a biological basis. As he showed, the typical mode of inheritance for political attitudes consists of approximately equal proportions of variance from additive genetic, shared environmental and unique environmental sources. This differs from other psychological variables, such as personality traits, which tend to be characterized by genetic and unique environmental sources of variation. By treating political attitudes as a model phenotype, Nick Martin was able to leverage the unique pattern of observed intergenerational transmission for political attitudes to reexamine the quintessential assumptions of the classical twin model. Specifically, by creatively leveraging the nuances of the genetic architecture of political attitudes, he was able to demonstrate the robustness of the equal environments assumption and suggest corrections to account for assortative mating. These advances have had a substantial impact on both the fields of political science, as well as behavioral and quantitative genetics.