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. 2017 Dec 20;50(3):169–178. doi: 10.1152/physiolgenomics.00044.2017

Evidence of genetic predisposition for metabolically healthy obesity and metabolically obese normal weight

Lam O Huang 1, Ruth J F Loos 2,3,4, Tuomas O Kilpeläinen 1,5,✉
PMCID: PMC6048453  PMID: 29341865

Abstract

Obesity has evolved into a global pandemic that constitutes a major threat to public health. The majority of obesity-related health care costs are due to cardiometabolic complications, such as insulin resistance, dyslipidemia, and hypertension, which are risk factors for Type 2 diabetes and cardiovascular disease. However, many obese individuals, often called metabolically healthy obese (MHO), seem to be protected from these cardiometabolic complications. Conversely, there is a group of individuals who suffer from cardiometabolic complications despite being of normal weight; a condition termed metabolically obese normal weight (MONW). Recent large-scale genomic studies have provided evidence that a number of genetic variants show an association with increased adiposity but a favorable cardiometabolic profile, an indicator for the genetic basis of the MHO and MONW phenotypes. Many of these loci are located in or near genes that implicate pathways involved in adipogenesis, fat distribution, insulin signaling, and insulin resistance. It has been suggested that a threshold for subcutaneous adipose tissue expandability may be at play in the manifestation of MHO and MONW, where expiry of adipose tissue storage capacity could lead to ectopic lipid accumulation in non-adipose tissues such as liver, muscle, heart, and pancreatic beta cells. Understanding the genetic aspects of the mechanisms that underpin MHO and MONW is crucial to define appropriate public health action points and to develop effective intervention measures.

Keywords: adiposity, cardiometabolic disease, genomics, metabolically healthy obesity, metabolically obese normal weight

INTRODUCTION

Obesity has been described as a global pandemic (43, 45, 58). The incidence of obesity has more than doubled worldwide since 1980 (66), posing a severe burden on the health care system. The majority of obesity-related health care costs are due to cardiometabolic comorbidities, such as insulin resistance, dyslipidemia, and hypertension, which are risk factors for Type 2 diabetes (T2D) and cardiovascular disease (61, 70).

Interestingly, some obese individuals appear to be protected against obesity-related cardiometabolic complications. This condition, first described in the 1980s (2, 54), is referred to as metabolically healthy obesity (MHO). Conversely, there are also individuals who have an elevated cardiometabolic risk that is similar to that of an unhealthy obese population, while having a body weight within the normal range. These individuals are referred to as metabolically obese normal weight (MONW) (46, 47).

Age, sex, ancestry, diet, smoking, and physical activity are known demographic and environmental factors contributing to MHO and MONW (11, 13, 28, 29, 42, 44). There are no estimates available for the heritability of these two conditions in current literature. Nevertheless, recent large-scale genomic studies have provided evidence that a number of genetic variants implicate an inverse relationship between increased adiposity and an unfavorable cardiometabolic profile, indicative of a genetic basis of the MHO and MONW phenotypes (25, 32, 33, 50, 67, 68). In this review, we will consolidate the increasing evidence of a genetic predisposition for MHO and MONW, provide comparison between studies, and unify shared hypotheses for the underlying mechanisms.

DEFINITIONS OF MHO AND MONW

Despite the simple notion, there is much debate on the definition of MHO (22, 23, 42, 57, 64). There are no universally accepted criteria for MHO (22, 23, 42, 57, 64), but it has been broadly defined as obesity, diagnosed by body mass index (BMI) ≥30 kg/m2, in the absence of cardiometabolic comorbidities (6, 22, 23, 42, 57, 64). The prevalence of MHO has been estimated to be 20–69% in the obese population (4, 7, 18, 21, 23, 37, 44, 55, 64). MHO is characterized by relatively high insulin sensitivity and healthy glycemic, lipid, inflammation, blood pressure, and hormonal profiles, with low incidence of cardiometabolic diseases, despite high adiposity (1, 8, 22, 24, 37).

Similar to MHO, various criteria have been used to define the MONW status. The condition is often described as normal weight (BMI < 25 kg/m2) with several cardiometabolic abnormalities typically seen in obese individuals (4, 5, 13, 17, 37). MONW is characterized by elevated triglycerides (TG), glycemic, and C-reactive protein (CRP) levels, reduced high-density lipoprotein cholesterol (HDL-C) and adiponectin levels, increased insulin resistance, and increased risk of T2D and cardiovascular disease (4, 5, 13, 17, 19, 37). The prevalence of MONW among normal weight individuals is estimated to be 4–25% (4, 7, 11, 18, 23, 37, 55, 64).

CURRENT EVIDENCE ON THE GENETIC BASIS OF MHO AND MONW

Despite the lack of consensus on the definitions of MHO and MONW, recent genomic studies have provided novel insights into the genetic basis of these two phenotypes by examining associations of genome-wide variants with adiposity and cardiometabolic traits. In two large-scale genome-wide association studies (GWAS) of body fat percentage (BFP), several variants were identified to cause a predisposition to increased adiposity but reduced cardiometabolic risk, representative of the MHO phenotype (25, 33). Other studies examined aggregate scores of insulin resistance loci and uncovered a link between genetic predisposition to insulin resistance and decreased adiposity, which implicates the MONW phenotype (32, 50, 67, 68). It is important to note that these two conditions are flipsides of the same coin, depending on which of the two alleles for the variant is considered to be the effect allele. In the following, we will discuss recent findings on the genetic determinants of these two paradoxical conditions.

GWAS of BFP identifies a favorable adiposity locus near the IRS1 gene.

In 2011, the first genome-wide meta-analysis of BFP was published, including up to 76,202 individuals of European and Indian Asian descent from 26 GWAS (25). Three loci were found to be associated with BFP, including a locus near the previously established FTO obesity gene (14, 51, 60, 65), and two novel loci, near SPRY2 and IRS1.

Opposite to what would be expected based on the known association between lower BFP and a favorable metabolic profile, the BFP-decreasing allele at the IRS1 locus was associated with lower HDL-C and higher TG levels and increased insulin resistance. The effect size of the IRS1 locus on BFP was significantly larger in men than in women, with each allele decreasing BFP by 0.20 and 0.06%, respectively. The association with HDL-C and TG was also greater in men than in women, whereas the association with insulin resistance was similar between men and women.

The BFP-decreasing allele of the IRS1 locus showed a significant reduction in subcutaneous adipose tissue (SAT) in men, but not in women. No association with visceral adipose tissue (VAT) was found in either sex. Consequently, the fat-decreasing allele at this locus was associated with a higher VAT/SAT ratio in men, but not in women. The BFP-decreasing allele at the IRS1 locus was also associated with lower adiponectin levels in men, but not in women, whereas no association was found for circulating leptin levels. Leptin and adiponectin are both hormones secreted by adipocytes, of which the former regulates appetite and food intake (27), whereas the latter glucose and lipid levels (69). Leptin levels are known to correlate positively with body fatness, whereas the correlation between body fatness and adiponectin levels is inverse (27, 69). Interestingly, studies have shown that transgenic overexpression of adiponectin permits healthy expansion of SAT in leptin-deficient (ob/ob) mice. Consequently, this prevents accumulation of lipids in the liver and retains insulin sensitivity (26). Hence, it was hypothesized that lower adiponectin level could be associated with reduced ability to expand SAT in men with BFP-decreasing allele of the IRS1 locus. This could then lead to a flux of lipids into liver, which may increase insulin resistance through lipotoxicity (63).

The variant most strongly associated with BFP near the IRS1 locus was located 500 kb upstream of the gene. In expression quantitative trait locus (eQTL) analyses, the BFP-decreasing allele exhibited reduced IRS1 expression in SAT and VAT, whereas no effect was seen in blood or liver. The reduced expression in SAT and VAT was found to be more significant in men than in women. In analyses for basal IRS1 gene expression, adipocytes of female mice exhibited higher Irs1 expression than those of male mice in both SAT and VAT, while in humans, women had higher expression of IRS1 in VAT than men, but no sex difference was observed in SAT. The higher basal levels of IRS1 in adipose tissue of women could be beneficial in buffering a modest level of impairment in IRS1 gene expression. Women also have a stronger drive to store fat subcutaneously than men, which could overcome a defect in IRS-1 function (25).

The IRS1 gene is likely to be involved in the regulation of insulin and insulin-like growth factor-1 action. Previous studies have shown that a single nucleotide polymorphism (SNP) (rs2943641) at the same locus is associated with reduced expression of IRS-1 protein and reduced insulin-induced phosphatidylinositol 3-OH kinase activity in skeletal muscle, which take part in insulin signal transduction (48). Knockout mice of Irs1 are insulin resistant and hyperinsulinemic, despite being lean (3, 59), consistent with the association between the BFP-decreasing IRS1 allele and an unfavorable cardiometabolic profile in humans.

Taken together, the BFP-decreasing allele at the locus near IRS1 exhibited features of the MONW phenotype. It was associated with an increased VAT/SAT ratio, adverse lipid profile, insulin resistance, reduced adiponectin levels, and increased risk of T2D and coronary artery disease (CAD) (Fig. 1). Conversely, aligning the results according to the BFP-increasing allele, the association pattern exhibits favorable adiposity and hence, is reminiscent of the MHO phenotype (Fig. 2). In contrast to IRS1, the BFP-increasing alleles of the loci in FTO and near SPRY2 showed associations with cardiometabolic traits that were consistent with the known association between increased adiposity and an unfavorable cardiometabolic profile (25). The discovery of the IRS1 locus implicated the first clear genetic link between increased adiposity and favorable cardiometabolic profile and suggested an interplay between subcutaneous fat expandability and improved insulin sensitivity as evidenced by epidemiological studies, eQTL analyses, and mouse studies. Amid the relatively modest sample size, as superseded by subsequent studies, it provides credible support to the genetic basis of MHO at multiple levels.

Fig. 1.

Fig. 1.

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Possible pathways and mechanisms involved at the locus near the IRS1 gene.

Fig. 2.

Fig. 2.

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Loci implicated in metabolically healthy obesity (MHO) and metabolically obese normal weight (MONW) and their association with cardiometabolic traits in meta-analyses of genome-wide association studies.

An extended GWAS of BFP identifies additional loci linked to favorable adiposity.

In 2016, an extended genome-wide meta-analysis of BFP, including up to 100,716 individuals from 56 studies, mainly of European ancestry, confirmed the associations for the IRS1, FTO, and SPRY2 loci and identified nine novel BFP-associated loci (33). Four of the novel loci, in or near MC4R, TMEM18, TUFM/SH2B1, and SEC16B, showed stronger association with BMI than BFP. The remaining five loci, in or near GRB14/COBLL1, TOMM40, IGF2BP1, PLA2G6/PICK1, and CRTC1, displayed stronger association with BFP than BMI (Fig. 3). As BMI represents the sum of fat and lean mass, whereas BFP is a ratio of body fat mass to body weight, the stronger association with BFP may indicate that the loci affect adiposity in particular.

Fig. 3.

Fig. 3.

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Comparison of effects of 12 body fat percentage (BFP) increasing loci on BFP and body mass index (BMI). Loci that have larger effects on BMI than BFP (above diagonal) are colored green, whereas loci with larger effects on BFP than BMI (below diagonal) are colored blue. The effect sizes are indicated in units of SD of inverse normally transformed traits (mean = 0, SD = 1). Adapted from Ref. (33).

The four novel loci that were associated more strongly with BMI than BFP had all been previously discovered in GWAS for BMI and were shown to influence body weight through their role in the central nervous system (10, 14, 31, 51, 56, 60, 65). As their BMI-increasing alleles were typically associated with an unfavorable cardiometabolic profile, we will not discuss them here. Of the five novel loci that were more strongly associated with BFP than BMI, the BFP-increasing alleles in three loci, near GRB14/COBLL1, TOMM40, and PLA2G6/PICK1, showed cardiometabolically protective effects (Fig. 2). The BFP-increasing allele at the locus near GRB14/COBLL1 was associated with an overall favorable cardiometabolic profile, including higher HDL-C and lower TG levels, and reduced risk of T2D and CAD. These protective associations may have been mediated by a favorable fat distribution, as the BFP-increasing allele was also associated with lower waist-to-hip ratio adjusted for body mass index (WHRadjBMI). In eQTL analyses, the BFP-increasing allele was associated with reduced adipose tissue expression of GRB14, which encodes a protein that binds directly to the insulin receptor. Grb14-deficient mice show improved glucose homeostasis and enhanced insulin action through increased phosphorylation of IRS1 in the liver and skeletal muscle (12). An increase in GRB14 expression has been found in adipose tissue from insulin-resistant mice and obese patients with T2D (9).

The BFP-increasing allele at the locus near a mitochondrial membrane protein-encoding TOMM40 gene showed favorable associations with some cardiometabolic traits, including a favorable lipid profile and reduced risk of CAD, while showing unfavorable associations with other traits, including higher WHRadjBMI, VAT, and liver fat and increased risk of T2D. The BFP-increasing variant is in modest linkage disequilibrium with two variants in the nearby APOE gene found associated with HDL-C, TG, and LDL-C (3). Conditional analyses were carried out to distinguish between the TOMM40 and APOE signals by conditioning the TOMM40 variant’s associations with BFP, HDL-C, TG, and LDL-C on the lipid-associated SNPs in APOE, and vice versa. After conditioning, the associations of the TOMM40 locus with BFP, HDL-C and TG were attenuated but remained significant, whereas the association with LDL-C disappeared (33). Conversely, there was no association between the APOE variants and BFP after conditioning on the TOMM40 variant, whereas the HDL-C, TG, and LDL-C associations remained significant after conditioning. These findings suggest that the BFP and lipid associations of the TOMM40 locus are partially independent on the APOE signal (33).

The BFP-increasing allele in the locus near PLA2G6/PICK1 was associated with lower TG levels in men and women, and with lower insulin levels and risk of T2D particularly in men. However, it was also associated with higher VAT in men. This locus harbors several genes that may drive the phenotypic associations. One strong candidate is the adipose tissue-expressed PICK1 gene: mice deficient in the gene show increased body fat and reduced lean mass, reduced TG levels, and increased insulin sensitivity, compensating for impaired insulin secretion (20).

To conclude, in addition to the previously identified IRS1 locus, this study identified three BFP-associated loci that displayed cross-phenotype association signatures that are reminiscent of the MHO phenotype. The BFP-increasing allele of the locus near GRB14/COBLL1 showed an overall favorable metabolic profile, similar to the previously identified IRS1 locus (25), whereas the loci near TOMM40/APOE and PLA2G6/PICK1 showed favorable associations with some cardiometabolic traits and unfavorable or no associations with others. The inconsistency of the BFP-increasing allele at the TOMM40/APOE and PLA2G6/PICK1 loci in inducing positive cardiometabolic outcomes is troubling for the interpretation of the functional role of these genes in metabolic health. Nevertheless, the identification of these three novel loci is a major step forward as it highlights the complexity of mechanisms underlying MHO and MONW, suggesting that there is a need for a more inclusive and less homogeneous interpretation of the underlying mechanisms implicated by loci related to MHO and MONW.

Follow-up of insulin resistance-associated loci reveals a genetic link to MONW.

Instead of approaching the evidence for MHO and MONW by screening adiposity-increasing loci for favorable effects on insulin resistance and other cardiometabolic traits, one can also approach this evidence by taking insulin resistance or other cardiometabolic traits as the starting point and screening for favorable adiposity effects. Indeed, a study published in 2014 examined whether GWAS-identified insulin resistance loci could be associated with a common, “lipodystrophy-like” phenotype (68). In monogenic lipodystrophy, patients have partial or complete lack of subcutaneous fat in combination with severe insulin resistance and dyslipidemia (16, 52, 53).

The associations of 19 known insulin resistance-increasing loci (50) with eight lipodystrophy-related traits were examined using results from published GWAS for BMI, VAT/SAT ratio, HDL-C, TG, hepatic steatosis and liver enzyme alanine transaminase (ALT), and circulating levels of adiponectin and sex-hormone binding globulin (SHBG). Hierarchical clustering was performed to group the 19 loci based on their associations with the eight traits to identify co-regulated and functionally related genes (68). Two clusters were observed. The first cluster contained 11 loci, in or near IRS1, GRB14, ARL15, FAM13A, LYPLAL1, PEPD, PDGFC, RSPO3, PPARG, TET2, and ANKRD55 (Fig. 2). A genetic risk score built using the insulin resistance-increasing alleles at these 11 loci was associated with lower BMI, HDL-C, adiponectin, and SHBG levels; higher TG, ALT, and VAT/SAT ratio; and greater hepatic steatosis. The second cluster contained five loci and was not associated with any of the tested traits, except with higher BMI, and the three remaining insulin resistance loci did not cluster with any other variants. Therefore, we will only focus on the cluster of 11 loci in this review.

The genetic score of the 11 loci was examined for associations with six additional cardiometabolic diseases and disease-related outcomes for which the risk was known to be increased in monogenic lipodystrophy, including T2D, CAD, systolic blood pressure (SBP), diastolic blood pressure (DBP), and carotid intima media thickness (cIMT) and carotid plague. In these analyses, including up to 69,828 individuals of European ancestry, the genetic score was associated with an increased risk of T2D and CAD and higher levels of SBP and DBP, but there was no association with either cIMT or carotid plaque.

As the score of 11 loci showed association with lower BMI, but higher VAT/SAT ratio, and elevated cardiometabolic risk, it was suggested that these loci may play a role in the development of a MONW-like phenotype. A separate meta-analysis of five studies, including up to 18,565 individuals of European descent, replicated the associations of the same 11 loci, except TET2, with lower adiposity but higher risk of T2D, hypertension, and heart disease (50). In 2016, the associations of the 11-locus score were confirmed in a larger sample size, including up to 164,609 individuals of European descent (67), showing an association pattern of the insulin resistance increasing alleles with lower adiposity yet an unfavorable cardiometabolic profile, resembling the MONW phenotype.

The hierarchical clustering of the loci associated with surrogate measures of insulin resistance suggests co-regulated pathways implicated within clusters, which is helpful in elucidating crucial aspects of the intertwined regulatory mechanisms at play. While the interpretation of the 11-locus cluster will require further pathway analyses and experimental model studies to be substantiated, this study opened up the possibility that an interplay between subcutaneous fat storage capacity and insulin resistance may contribute to the MONW phenotype.

Novel insulin resistance loci highlight a role for peripheral adipose storage in MONW.

Multiple novel insulin resistance loci were identified in 2016 through a screening approach that combined published GWAS summary results for fasting insulin, TG, and HDL-C levels, which are hallmarks of insulin resistance. More specifically, GWAS summary results from up to 188,577 individuals of European ancestry were screened for loci showing association with higher fasting insulin (P < 0.005), higher TG (P < 0.005), and lower HDL-C levels (P < 0.005) (32). This approach identified 53 insulin resistance loci that were subsequently combined into a genetic score. The 53-locus score was associated with lower BFP and BMI, lower hip circumference and gynoid and leg fat mass, and higher waist circumference and risk of T2D. The authors proposed that the association with smaller hip circumference and gynoid and leg fat could indicate an impaired ability to expand the peripheral fat compartment (32). Furthermore, as the genetic score was associated with higher levels of ALT and γ-glutamyltransferase, it was hypothesized that the score may be associated with hepatic lipid deposition due to failure of lipid storage in SAT. Analyses in women with familial partial lipodystrophy type 1 (FPLD1) showed a higher burden of the alleles at these 53 loci, suggesting that the polygenic predisposition of these 53 loci may contribute to the FPLD1 phenotype. An overlap was also found with regulatory regions of lipodystrophy in adipose tissues, and pathway analysis and cellular models indicated the involvement of some of the insulin resistance loci with adipocyte gene expression and lipid accumulation.

This study on insulin resistance harvested a large number of loci due to an increase in sample size and a novel analysis strategy focusing on a combination of fasting insulin, triglycerides, and HDL-cholesterol. The association of the identified insulin resistance loci as a genetic score with peripheral fat storage capacity was inferred through concurrent measures of fat distribution and liver markers in the studied population. These epidemiological observations were partly supported by results from analyses of pathway enrichment and from experimental studies in cell cultures. Hence, this study provides strong evidence supporting a link between subcutaneous adipose tissue expandability and insulin resistance as previously suggested by rodent models.

DISCUSSION

With the increasing evidence of a genetic link between increased adiposity and a favorable cardiometabolic profile, or conversely, between decreased adiposity and an unfavorable cardiometabolic profile, a genetic basis of the MHO and MONW phenotypes is substantiated. This review provides a summary of the findings on genetic loci that contribute to MHO and MONW reported so far.

A number of physiological pathways, including adipogenesis, angiogenesis, adipose tissue dysfunction and expandability, adipose inflammation, macrophage infiltration and activation, lipid oxidative capacity, fat distribution, ectopic fat accumulation, and impaired mitochondrial function, have been suggested to contribute to the metabolic heterogeneity seen among obese and normal-weight individuals (8, 15, 35, 36, 40, 63). These findings have been largely based on studies conducted in transgenic rodent models (15) or human cell lines (35, 36), and some in obesity-discordant monozygotic twins (49). The genomic studies published so far have highlighted the involvement of four main mechanisms in MHO and MONW: insulin signaling, insulin resistance, adipogenesis, and fat distribution. The role of insulin signaling and insulin resistance was implicated by the favorable cardiometabolic effects of adiposity-increasing loci that have important roles in the insulin receptor signaling pathway, such as IRS1 and GRB14/COBLL1 (25, 33), as well as findings on the relationship between genetic predisposition to insulin resistance and decreased adiposity (32, 50, 68). The link between insulin resistance and decreased adiposity was hypothesized to reflect a common, low-penetrant “lipodystrophy-like” syndrome that may share underlying mechanisms with monogenic lipodystrophies (32, 50, 67, 68). The role of fat distribution was implicated by the association of aggregate scores of insulin resistance-increasing loci with reduced peripheral SAT (25, 32, 33, 50, 67, 68). The importance of adipogenesis was shown in pathway analyses and knockdown experiments for some of the implicated genes, where adipocyte gene expression or lipid storage capacity was affected (32, 38, 62).

One hypothesis proposed to underlie the link between genetic predisposition to insulin resistance and MONW in the studies we reviewed is that insulin resistance-increasing loci may be involved in determining an individual threshold for SAT expandability (63). As subcutaneous fat storage space expires, lipid starts to accumulate ectopically in nonadipose tissues, such as the liver and skeletal muscle. This may disrupt insulin signaling in liver and muscle, leading to whole-body insulin resistance and dyslipidemia (25, 48) through a lipotoxic mechanism (63). Adipogenesis allows healthy expansion of SAT, preventing ectopic lipid deposition (25, 32, 33, 50, 67, 68). These intertwined mechanisms may play an important role in the development of MHO and MONW phenotypes. However, causality between subcutaneous fat storage capacity and insulin resistance could not be deduced from the studies performed so far (32, 50, 68). Furthermore, we noted that some loci implicated in MHO are associated with decreased WHRadjBMI, while others are associated with increased WHRadjBMI (Fig. 2). This suggests the presence of other mechanisms than fat distribution and subcutaneous fat expansion in mediating the paradoxical link between increased adiposity and a favorable cardiometabolic profile. Some identified SNPs in linkage disequilibrium with other SNPs in nearby genes might also exhibit heterogeneous effects, as seen for the locus near TOMM40/APOE (33), or show pleiotropic effects on adiposity and cardiometabolic traits, which could provide an alternative explanation for the observed results. Extended gene discovery studies focusing on specific combinations of adiposity and cardiometabolic traits, along with analyses of the enrichment of loci representing such association signatures in biological pathways, will be needed to unravel the mechanisms underlying the heterogeneous association signatures of loci implicated in MHO and MONW. Follow-up analyses using more refined human phenotypes and studies in experimental models will be required to validate such novel mechanistic insights.

Understanding the underlying mechanisms that lead to MHO and MONW is important to explain why not all obese individuals develop metabolic impairments and to find new ways to prevent development of cardiometabolic disease among those who are already obese. Identifying genetic determinants of MHO and MONW may open up new avenues for drug development and for defining public health action points. For example, the thiazolidinedione class of antidiabetic drugs has been shown to be capable of stimulating adipose tissue differentiation by activating PPARG, which leads to increased body weight but improved insulin sensitivity at the same time (41). If individuals can be identified with a genetic predisposition to either MHO or MONW, tailored medical intervention such as these could be selectively used for prevention and treatment.

GRANTS

This work was supported by Danish Council for Independent Research (DFF) Grant 6110-00183 and Novo Nordisk Foundation Grant NNF17OC0026848.

DISCLOSURES

No conflicts of interest, financial or otherwise, are declared by the authors.

AUTHOR CONTRIBUTIONS

L.O.H. prepared figures; L.O.H. and T.O.K. drafted manuscript; L.O.H., R.J.F.L., and T.O.K. edited and revised manuscript; L.O.H., R.J.F.L., and T.O.K. approved final version of manuscript; R.J.F.L. and T.O.K. conceived and designed research.

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