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Evidence for HTR1A and LHPP as interacting genetic risk factors in major depression

Abstract

The HTR1A −1019C>G genotype was associated with major depression in the Utah population. Linkage analysis on Utah pedigrees with strong family histories of major depression including only cases with the HTR1A −1019G allele revealed a linkage peak on chromosome 10 (maximum HLOD=4.4). Sequencing of all known genes in the linkage region revealed disease-segregating single-nucleotide polymorphisms (SNPs) in LHPP. LHPP SNPs were also associated with major depression in both Utah and Ashkenazi populations. Consistent with the linkage evidence, LHPP associations depended on HTR1A genotype. Lhpp or a product of a collinear brain-specific transcript, therefore, may interact with Htr1a in the pathogenesis of major depression.

Introduction

Mood disorders, of which major depressive disorder (MDD) is the most common, affect one person in five during their lifetime. The World Health Organization estimates that depression is currently the fourth most important worldwide cause of disability-adjusted life year loss, and that it will become the second most important cause by 2020.1 Pharmaceutical treatment of depression is frequently inadequate. Using the current best treatments, one-third of patients or more do not achieve remission even after several months of treatment.2 When today's drugs do help patients achieve remission from their depression, the onset of action is over a period of weeks, and there appears to be an increased risk of suicide during initial antidepressant therapy, although this risk may be less than that just prior to therapy initiation.3 Furthermore, there are high recurrence rates—approximately 85% of patients who achieve remission will suffer another episode of MDD.4 Finally, currently available antidepressants are associated with side effects that lead some patients to stop taking their medications at risk of sinking back (further) into depression, and to morbidity in others.5

Currently available antidepressants work primarily by increasing the activity of the neurotransmitters, serotonin and norepinephrine, in synapses.5 Some medications inhibit the degradation of these molecules, others decrease removal of neurotransmitters from the synaptic space, and some medications stimulate norepinephrine release or inhibit negative feedback of serotonin signaling. Because these medications are all based on a single principle, the strength and range of their efficacy is similar. The improvements of the last half-century have involved the development of safer and more tolerable drugs. However, despite this, today’s drugs are neither completely safe nor completely tolerable for many patients. There is considerable need for new drugs that are effective in a broader range of patients (particularly for patients whose depression is resistant to available pharmaceuticals), that have a faster onset of action, that are safer and more tolerable or that complement the efficacy of existing drugs. It is unlikely that a substantial further improvement in any of these dimensions will be achieved through the development of additional serotonergic or noradrenergic agents.

Identifying the underlying genetic components of depression can open new avenues for the development of novel depression drugs. Specifically, if a genetic variant segregates with MDD in families, the gene in which that variant occurs is likely to be involved in the pathobiology of disease. Such a gene can be a target for development of novel antidepressants, or lead to identification of previously unknown physiological pathways that can be modulated for effective therapy of depression.

Materials and methods

Subjects and linkage analysis

The ascertainment and characteristics of a majority of the linkage pedigrees has been described.6 Informed consent was obtained from each subject. The institutional review boards of Intermountain Health Care and Valley Mental Health approved the research protocol. Two meaningful differences between the present study and our previously published work are as following: first, that the definition of affected status in this study did not include bipolar disorder; second, that 22 additional pedigrees were ascertained using the previous criteria. The average pedigree size was 16 individuals (range 6–55) including a mean of 8 affected individuals (range 4–31). The analysis leading to discovery of the chromosome 10 linkage region included 1054 individuals (744 female subjects and 310 male subjects) with MDD (DSM-IV-TR sections 296.2x or 296.3x). Affected individuals were genotyped and genome-wide linkage analysis was performed as described,6 except that only individuals carrying one or two HTR1A −1019G alleles were assigned affected status.

Polymorphism discovery in linked pedigrees

Genomic DNA from members of the MDD pedigrees with the strongest linkage evidence was resequenced. From each pedigree, two female subjects with MDD, carrying one or two HTR1A −1019G alleles, and sharing a chromosome 10 haplotype that cosegregates with the disease were selected. This allowed direct determination of whether each variant found during resequencing cosegregated with the disease. In the case of common variants, using this strategy to predict cosegregation could overestimate the actual cosegregation of the variant with disease, but for such variants resequencing of additional family members was undertaken to verify that the variant was indeed on the disease associated haplotype. Haplotype sharing was determined using the program MCLINK7 during linkage analysis.

Thirty-six genes (Supplementary Table S1) were identified within the minimal recombinant region using both publicly available NCBI human genome assemblies and assembly of publicly available sequence data using a proprietary algorithm (Compugen, Israel). Several genes were extended using rapid amplification of cDNA ends.

PCR amplification was used to generate products to screen for segregating variants in all exons and proximal promoter regions of the identified genes. When possible to conserve DNA, a primary amplicon was created using genomic DNA (10–20 ng) and a 25-cycle amplification. The primary amplicon was then diluted 45-fold and used as template to amplify several secondary amplicons using nested M13-tailed primers for an additional 25 cycles. However, many amplicons were sequenced after only a single round of amplification with M13-tailed primers using 10 ng genomic DNA and 35 cycles. All primers used to amplify LHPP exons are shown in Supplementary Materials and methods. All samples were amplified with Taq Platinum (Invitrogen, Carlsbad, CA, USA) DNA polymerase. PCR cycles included an initial denaturation at 96 °C (12 s), annealing at 57 °C (15 s) and extension at 72 °C (30–60 s). Excess primers and deoxynucleotide triphosphates from M13-tailed PCR products were digested with exonuclease I (United States Biochemicals, Cleveland, OH, USA) and shrimp alkaline phosphatase (Amersham, Piscataway, NJ, USA). PCR products were sequenced with M13 forward and reverse fluorescent Big Dye-labeled primers (Applied Biosystems, Foster City, CA, USA) on Applied Biosystems 3730 sequencers.

Statistical analysis

Based on several prior associations with MDD or related phenotypes,8, 9, 10, 11, 12, 13, 14, 15 the one-tailed Fisher's exact test (α=0.05) was used to test the association of major depression in the Utah population with HTR1A1019G allele or –1019GG genotype.

To establish the evidence that LHPP acts as a depression gene in the chromosome 10 linkage region, allele frequencies on the 22 chromosomes that cosegregated with MDD were compared, using the two-tailed Fisher's exact test (α=0.05), to frequencies in three sets of control chromosomes. A first set of 60 control chromosomes included the 12 non-segregating chromosomes from genotyped, affected pedigree members and 48 chromosomes from 24 unrelated individuals from Utah CEPH pedigrees. The second set of 180 control chromosomes was from 90 additional Utah CEPH pedigree grandparents. The third set of 708 control chromosomes was from 354 unrelated samples collected in Utah. Replication was used, rather than α-level adjustment, to avoid an inflated type I error rate.

For population association analyses, cases were individuals with confirmed diagnosis of MDD (DSM-IV-TR sections 296.2x or 296.3x). Ashkenazi samples were individuals who reported four grandparents of Ashkenazi descent. These samples were collected by PrecisionMed (Solana Beach, CA, USA). Utah and Ashkenazi individuals ascertained without respect to depression status were used as controls. Initial logistic regression models included LHPP genotype, HTR1A genotype, gender and both genotype-by-genotype and genotype-by-gender interaction terms. LHPP and HTR1A genotypes were each dichotomized such that risk allele carriers (heterozygous or homozygous) were compared to non-carriers. Final logistic regression models were derived through a stepwise backward elimination process using α=0.10. The main effect of LHPP genotype was the primary comparison of interest. No α-level adjustment was made for testing several markers within a single gene. Logistic regression odds ratios (OR) and 95% confidence intervals (CI) were calculated using JMP 5.1 (SAS Institute, Cary, NC,USA).

Phylogenetic tree construction

A database of human Refseq protein sequences16 was searched using a hidden Markov model that describes the gene family (Pfam00702) and the Hmmersearch algorithm.17 Sequences matching the hidden Markov model were aligned using the same model and Hmmeralign.18 A phylogenetic tree (Supplementary Figure S1) was constructed from gap-free regions of the mutiple sequence alignment by a protein distance matrix method using the Protdist and Fitch algorithms from the Phylip software.19 Sixty amino-acid positions from the alignment were used. The tree was visualized using Treeview.19

Northern blot

A pre-made poly(A) RNA Northern blot (Ambion, Austin, TX, USA) was probed with amplified DNA produced by PCR using the following primers.

Forward: IndexTermGAATCTCCCAAATCCCAGAACTCA

Reverse: IndexTermACACCGGGCATGACACCTTCAAGT

Amplified DNA was labeled using an AmbionStrip-EZ DNA kit (Ambion) and α-32P-labeled dATP. The blot was hybridized overnight at 42 °C in ULTRAhyb Ultrasensitive Hybridization Buffer (Ambion), washed twice for 15 min at low stringency (2 × SSPE, 0.1% SDS) and twice for 15 min at high stringency (0.1 × SSPE, 0.1% SDS). All procedures were carried out according to the manufacturer's instructions.

Quantitative reverse transcription PCR

Human total RNAs were purchased from either Ambion or BD Biosciences (Franklin Lakes, NJ, USA). Reverse transcription and PCR were conducted using the Invitrogen Platinum Thermoscript One Step System qRTPCR kit following the manufacturer's instructions. Fifty nanograms of DNase-treated total RNA were used as a template for each reaction. All threshold cycle readings were normalized to 28S rRNA.

A schematic of LHPP transcripts is shown in Figure 4. The primers and probes used are provided as Supplementary Materials and methods.

Characterization of EF151005

IMAGE clones h3175509, h5194531, h5197955 and h4565014 were obtained from the American Type Culture Collection (Manassas, VA, USA). DNA sequencing was performed with M13 forward and reverse fluorescent (Big Dye, ABI) dye-labeled primers.

RNA ligase-mediated rapid amplification of cDNA ends was performed using the FirstChoice RLM-RACE kit (Ambion) on 10 μg human spinal cord total RNA (BD Biosciences Clontech, Palo Alto, CA, USA) according to the manufacturer's instructions. Nested PCR used the following gene-specific primers:

Outer: IndexTermTCTCCCACTGTATGCTCCTTCCA

Inner: IndexTermCTCTGCCACTTCATCTGCAGGT

Products were separated by electrophoresis and sequenced as above.

Two exon-bridging reverse transcription-PCR experiments were conducted to learn whether the unique exon of EF151005 also occurred naturally in alternatively spliced forms of LHPP. In a first experiment, PCR was conducted using a forward primer within an upstream exon of LHPP (IndexTermTGCAAGCGATAGGAGTGGAA) and a reverse primer within the unique exon of EF151005 (IndexTermCCACCCCATGCCATCAA). In a second experiment, PCR was conducted using the same forward primer and a reverse primer in the exon common to LHPP and EF151005 (IndexTermCACGTACCCATCAGCCTTCAC). Amplification products were sequenced as above to determine whether any unique sequence from EF151005 was included. Each of these experiments was conducted on cDNA prepared from each of three separate lots of human spinal cord mRNA (BD Biosciences Clontech).

Results

Serotonin receptor 1A-conditional genetic analysis

The serotonin receptor 1A (Htr1a) is a therapeutic target in the management of depressive and anxiety disorders.21 A common promoter polymorphism, HTR1A −1019C>G, has been described.22 Results of in vitro experiments suggest that the minor allele (−1019G) prevents binding of a transcriptional repressor, resulting in enhanced receptor expression.8 The −1019G allele or the homozygous −1019GG genotype has been associated with depression, suicide, bipolar disorder, panic disorder with agoraphobia, neuroticism and decreased antidepressant response.8, 9, 10, 11, 12, 13, 14, 15

We tested the hypothesis that the HTR1A −1019G allele increases depression risk in a Utah population. Observed frequencies of −1019G allele (350/688) and −1019GG genotype (89/344) were 1.10- and 1.34-fold higher among unrelated individuals affected with MDD compared to unaffected individuals (312/672 and 65/336; one-tailed Fisher's exact test P=0.05 and 0.02, respectively). There was no significant difference in allele frequencies between genders in cases or controls. Thereafter, we conducted genome-wide linkage analysis conditioned on carriage of the HTR1A −1019G allele. Only individuals with MDD and also carrying one or two copies of the HTR1A −1019G risk allele were considered affected.

In this HTR1A-conditional linkage analysis using a dominant genetic model, we observed evidence of linkage on chromosome 10 with a maximum HLOD of 2.9 at D10S1222 and D10S1676 (Figure 1a). Using a gender specific model that considered only affected female subjects, the maximum HLOD was 3.1 at D10S1222 (Figure 1b). There was no linkage evidence in this region when only affected male subjects were considered in the analysis (Supplementary Figure S2). The linkage evidence on chromosome 12 in analyses considering only affected male subjects, with a maximum HLOD of 3.3 at 12-MYR0332, corresponds to our previously described linkage in this population of MDD to apoptosis protease activating factor 1.6, 23 We observed an even higher HLOD of 4.6 at 12-MYR0332 without considering an interaction with HTR1A −1019G, thus we assume that there is no interaction between apoptosis protease activating factor 1 and HTR1A. No other significant or suggestive linkage evidence was observed using a dominant model restricted to male subjects. There was no significant or suggestive conditional linkage evidence using gender-neutral or gender-specific recessive genetic models (Supplementary Figures S3–S5). Genome scan results are provided in Supplementary Table S2.

Figure 1
figure1

Results of genomic search for loci linked to MDD. Multipoint HLOD scores for the dominant, HTR1A −1019G-conditional model are plotted on the y axis, and marker positions (in cM) are plotted on the x axis. Vertical dashed lines delimit the chromosomes. (a) HLOD for gender-neutral linkage. (b) HLOD for females-only linkage. MDD, major depressive disorder.

On inclusion of data from a denser marker set across the central 26 cM interval (D10S1237-D10S1700), linkage evidence increased to a peak HLOD of 4.4 at D10S575 when the model was restricted to female subjects (Figure 2; Supplementary Table S3). Linkage evidence did not improve with additional marker data in a gender-neutral model (Supplementary Table S3). We, therefore, chose to continue gene discovery efforts focusing on the pedigrees contributing to the female-only linkage evidence. Without considering the HTR1A genotype, but still using a female-only dominant genetic model we observed to an extent lesser linkage evidence with a peak HLOD of 3.4 at D10S214 (Supplementary Table S3). When the affected individuals included only female subjects carrying at least one HTR1A −1019G allele, the HLOD increased and the linkage region narrowed (as defined by a drop of HLOD of either one or two from the peak value), better localizing the disease gene. More importantly, conditioning on HTR1A revealed linkage evidence in a distinct set of pedigrees. Further investigation of pedigrees that showed linkage evidence dependent on the HTR1A −1019G allele was crucial to the discovery of single-nucleotide polymorphism (SNPs) segregating with major depression in LHPP.

Figure 2
figure2

Linkage analysis of chromosomal region 10q26.2–10qter with additional markers (HTR1A-conditional, dominant model and female-only). Black dots correspond to the position of markers used in the analysis. The dashed line indicates the region with boundaries determined by recombination events in the pedigrees with the strongest linkage evidence. The arrow indicates the approximate position of LHPP.

Each gene in the linkage region (Supplementary Table S1) was resequenced using genomic DNA from 32 affected female subjects—two representatives from each of the 16 pedigrees. These pedigrees were selected on the basis of a familial HLOD of at least 0.4. Among these pedigrees, six had not shown linkage evidence without conditioning the model on the HTR1A −1019G allele. The frequencies of variant alleles of the chromosome 10 linkage region among the 22 chromosomes that segregated with MDD (‘linked chromosomes’) within these pedigrees were compared to the frequencies among 60 control chromosomes (Table 1). A risk allele significantly (two-tailed Fisher's exact test, α=0.05) overrepresented on linked chromosomes was identified for seven SNPs within LHPP and six SNPs in other genes within the region. A statistical trend was observed for an eighth LHPP SNP but not for any other SNP in another gene. Of the LHPP SNPs, two pairs (rs2459213 and rs2491156, rs10794134 and rs3824810) were each in complete linkage disequilibrium, and so only one of each pair was analyzed further. Variant allele frequencies among the chromosomes that segregated with MDD were next compared to the frequencies in a separate set of 180 control chromosomes (Table 1). Variant alleles of only three SNPs, all in LHPP, were significantly overrepresented on the chromosomes that segregated with MDD in this comparison. These three LHPP SNPs, and two others, were significantly overrepresented on the disease chromosomes compared to a third set of 708 control chromosomes. This is the primary evidence supporting LHPP as the gene underlying the MDD linkage evidence on chromosome 10. LHPP haplotypes on the chromosomes segregating with disease were quite diverse. Fifteen distinct SNP haplotypes segregated with MDD among affected female subjects in the 16 pedigrees, and no haplotype was common to more than 3 pedigrees (Supplementary Table S4). This pattern is consistent with multiple origins or allelic heterogeneity of functional variants.

Table 1 Linkage evidence for LHPP on chromosome 10

To further support the relationship between LHPP genotypes and MDD, genetic association studies comparing genotype frequencies between individuals affected with MDD and healthy controls were performed in two populations, neither including the families that showed evidence of linkage on chromosome 10. Logistic regression models included LHPP and HTR1A genotypes, gender and interaction terms (genotype-by-genotype and genotype-by-gender). To reflect the dominant genetic model of LHPP linkage on the HTR1A1019G allele, both genotypes were grouped into dichotomous variables such that carriers of a risk allele (heterozygous or homozygous) were compared to non-carriers.

Unrelated cases were selected from the Utah families used for linkage analysis that did not show evidence of linkage on chromosome 10, or that were too small to be considered in the linkage analysis. In this Utah sample set, two markers were associated with MDD: rs10794134 (adjusted OR for the T allele 1.40, 95% CI 1.00–1.94, P=0.05) and ss68074662 (adjusted OR for the A allele 2.03, 95% CI 0.99–4.48, P=0.05). For each marker, the frequency of LHPP risk allele carriage was highest among HTR1A −1019G-positive cases and approximately equal among all other groups (Table 2). Additionally, the same LHPP alleles were both linked to and associated with MDD in the Utah population. There was an rs10794134 genotype-by-gender interaction, mainly reflecting different LHPP genotype distributions between male subjects and female subjects of HTR1A −1019CC genotype. In the Ashkenazi population, two markers were associated with MDD: rs10794134 (adjusted OR for the T allele 0.59, 95% CI 0.35–0.99, P=0.05) and rs12265012 (adjusted OR for the A allele 0.43, 95% CI 0.24–0.75, P=0.004). For each marker, one LHPP allele was underrepresented among HTR1A −1019G-positive cases, and was approximately equally frequent among all other groups (Table 2). There was no association with MDD for either rs12265012 in the Utah population, or for ss68074662 in the Ashkenazi population (Table 2).

Table 2 Joint distributions of HTR1A and LHPP genotypes among MDD patients and controls in the Utah and Ashkenazi populations

Characterization of LHPP transcripts

LHPP encodes an enzyme known as phospholysine phosphohistidine inorganic pyrophosphate phosphatase (Lhpp), which was originally purified from swine brain.24 and subsequently purified from several additional mammalian organs.25, 26, 27, 28 A human LHPP cDNA has been cloned, and functional human Lhpp has been purified following heterologous expression in Escherichia coli.29 Lhpp has been characterized in vitro as efficiently catalyzing the hydrolysis of P–N bonds in phosphohistidine and phospholysine, and less efficiently catalyzing the hydrolysis of P–N or P–O bonds in imidodiphosphate and pyrophosphate, respectively.30

Expression of a 1.8 kb LHPP mRNA was previously observed in brain, liver and kidney.29 Using a probe from the 3′ end of LHPP mRNA, we detected full-length LHPP mRNA as an approximately 1.7 kb transcript in multiple tissues. In addition, an approximately 1.1 kb transcript was very abundant in the brain, observed at low levels in skeletal muscle and spleen but absent in other tissues (Figure 3a). Affymetrix U133 Plus and U133Av2 microarrays each include probe sets from the 3′ end of LHPP mRNA. Among a panel of tissue-specific mRNA libraries hybridized to these microarrays, statistically significant signals (α=10−12) for the LHPP probe sets were observed using 18/19 central nervous system samples (the exception was a fetal brain sample) and 0/49 other samples (Supplementary Tables S5 and S6). These data suggested existence of a collinear mRNA species specifically or selectively expressed in the brain.

Figure 3
figure3

Tissue expression patterns of LHPP transcripts. (a) Northern blot using a probe from the 3′ exon shared by four transcripts (EF151005, BG759116, LHPP and LHPP-SV1). (b) Heatmap of reverse transcription PCR results. Tissues were clustered using the hierarchical clustering algorithm in JMP 5.1 software (SAS Institute) with default settings. Scale: threshold cycle 17.5 (blue)–40 (red). Non-CNS tissues, left to right: adrenal gland, uterus, kidney, lung, liver, testis, heart, skeletal muscle, heart, small intestine, liver, prostate, trachea, thyroid gland, placenta, kidney, salivary gland, peripheral leukocytes, thymus, fetal liver, lung and spleen. CNS tissues, left to right: amygdala, globus pallidus, whole brain, orbital frontal cortex, spinal cord, hippocampus, hypothalamus, basal ganglia, caudate nucleus, medulla, pons, prefrontal cortex, thalamus, whole brain and spinal cord.

Potential collinear transcripts were identified by mining the Genecarta transcriptome database (Compugen, Israel), and experimentally. Nineteen transcripts (including full-length LHPP) were identified. Nine were eliminated from further analysis: the evidence for eight was limited to a single expressed sequence tag each and we were unable to develop a reliable assay to detect expression of the other. The tissue distributions of the remaining 10 transcripts were determined using quantitative reverse transcription PCR. These transcripts are shown in Figure 4. Expression levels were categorized according to threshold cycle: very high (<20), high (20–25), moderate (25–30), low (30–35), very low/questionable (35–40) or not detected (no signal above background after 40 cycles). Because of the linkage and association of LHPP variants to MDD, there was particular focus on measuring expression of these transcripts in the brain (Figure 3b).

Figure 4
figure4

Genetic markers, transcripts and LD structure in the LHPP gene. Red lines indicate genetic marker positions. D10S2322 delineated the centromeric end of the linkage region, based on recombinants observed in each of the four pedigrees having high familial LOD. Blue lines indicate exon positions; thinner or thicker lines indicate partial skipping due to alternative splicing or transcriptional read-through, respectively. LD was visualized using Haploview software20 accessed through the International HapMap Project website (http://www.hapmap.org) on 13 May 2005. LD magnitude is represented by red squares without numbers (D′=1, LOD>2), light blue squares (D′=1, LOD 2) and D′-values. LD, linkage disequilibrium.

Two transcripts are each comprised of a unique 5′ exon spliced to the 3′ exon of LHPP (Figure 4), neither of which could encode an Lhpp-like protein. The 3′ shared exon contains two potential open reading frames of at least 100 amino acids. Neither predicted protein shares meaningful homology with any known protein. EF151005 (1.2 kb) was detected as a high or very high abundance transcript in all central nervous system samples except for fetal brain (moderate), and as a moderate or low abundance transcript in other tissues except for lung (not detected). These results were replicated using a second quantitative reverse transcription PCR assay (not shown). Based on its expression pattern and length, EF151005 is a very strong candidate to explain our gel and microarray hybridization results in the brain. We sequenced several clones of EF151005 to confirm the sequence predicted from database mining, performed RNA ligase-mediated rapid amplification of cDNA ends on a pool of human spinal cord RNA to determine its 5′ends (annotated in Entrez Nucleotide), and conducted exon-bridging reverse transcriptase PCR experiments to determine that the unique exon of EF151005 was not observed in transcripts that also contain upstream LHPP exons (data not shown). BG759116 (1.1 kb, we have not confirmed the complete sequence of this species) was detected as a low abundance transcript in a few samples. The strongest signal was observed in spleen, consistent with the hematopoietic sources of the transcriptome database support for this transcript. It may explain the lower band observed in spleen by gel hybridization.

Full-length LHPP was detected as a high or moderate abundance transcript in all samples except fetal liver (not detected). Of note, the first 137 nucleotides of the published sequence29 do not match chromosome 10 and also were not found in any LHPP expressed sequence tag. Three splice variants of LHPP each encode truncated proteins containing one or both haloacid dehydrogenase domains that may be the catalytic regions of Lhpp protein (Figure 4). LHPP-SV1, which arises from skipping of LHPP exon 6, was detected as a high abundance transcript in all samples. Expression patterns of full-length LHPP and this splice variant were generally similar. The upper band observed by gel hybridization probably reflects both species. LHPP-SV2, which results from read-through transcription of approximately 111 nucleotides after LHPP exon 6, was detected as a moderate abundance transcript in most central nervous system samples, as well as in several other tissues. LHPP-SV3, which results from read-through transcription of approximately 190 nucleotides after LHPP exon 5, was detected as a moderate abundance transcript in a few samples, and as a low abundance transcript in all others.

LHPP-SV4 contains LHPP exon 3, a cryptic exon from within LHPP intron 6 and the first 39 and last 367 nucleotides of LHPP exon 7. It has no apparent open reading frame. This species was detected as a moderate abundance transcript in all central nervous system samples, as well as in several other tissues. LHPP-SV2, LHPP-SV3 and LHPP-SV4 are not known to include the probe sequences used in gel or microarray hybridization. In addition, three transcripts arise from LHPP intronic or proximal sequences. BX346339 (we have not confirmed the complete sequence of this species) was detected only as a low abundance transcript. AK127935 and AW867792 were detected as moderate abundance transcripts in most samples.

Discussion

Following observation of increased frequency of the HTR1A −1019G allele among MDD cases in a Utah population, we conditioned genome-wide linkage analysis for MDD in that population on carriage of the G allele. That analysis suggested the presence of a genetic risk factor for MDD on chromosome 10 (Figures 1, 2). Several SNPs in LHPP were linked to MDD (Table 1), particularly in pedigrees in which at least four affected female subjects carried the HTR1A −1019G allele. Some of these SNPs were also associated with MDD in each of Utah and Ashkenazi populations (Table 2). Both familial linkage and population association of LHPP SNPs to MDD depended on HTR1A genotype. The combined genetic evidence suggests that a LHPP product may interact with Htr1a in a pathogenetic pathway of MDD. Alternatively, these two gene products may play roles in two different compensatory pathways, requiring disruption of both to result in disease.

The LHPP polymorphisms associated with MDD differ between Utah and Ashkenazi populations, and opposite alleles at rs10794134 were associated with MDD between the two populations. This sort of situation is not unusual in psychiatric genetics, in fact it has been observed for most of the genes that have been linked to schizophrenia.31 One parsimonious explanation for our association study results is that functional alleles of LHPP arose on different haplotypes in the Utah and Ashkenazi populations. Other factors may lead to observation of association between a complex disease and different markers or alleles within the same gene. For example, a particular marker or allele may have a variable phenotype depending on genetic and environmental background.

Common genetic risk factors for diseases such as MDD will lead to only modest increases of disease prevalence, largely due to dependence on interaction with other genes and non-genetic risk factors. The complexity of these diseases partially explains the difficulty in identifying susceptibility genes. One approach to gene discovery within a heterogenous disease is to condition genetic analysis on the basis of a reasonable independent criterion. The present work was based on a supposition that previously unknown gene–gene interactions could be discovered by conditioning familial linkage analysis on a genotype that is associated with disease in the population from which the linkage pedigrees were ascertained. Several linkage regions for complex diseases have been reported using similar analytical approaches. The IDDM4 locus for type I diabetes mellitus was identified by stratifying linkage analysis according to HLA DR3 and DR4 genotypes.32 Several novel linkage regions for MDD were observed when pedigrees were dichotomized based on linkage evidence at D2S2208, the marker that produced the maximum multipoint LOD score in that set of families.33 One of these novel regions peaked at D10S1656, a marker about 300 kb centromeric of LHPP. A schizophrenia linkage region was revealed when analysis was conditioned on TNFA promoter haplotypes.34 Recently, a novel obesity linkage region was discovered by conditioning analysis on a SNP in TBC1D1, itself recently linked to obesity in the same pedigrees.35 However, none of these conditional linkage analyses have led to a gene discovery. The HTR1A-conditional linkage of LHPP to MDD is the first for which a linked gene in an interacting region has been identified, and the first for which the gene–gene interaction has been further supported by showing conditional association in population studies. This work demonstrates that novel epistatic risk genes for common diseases can be discovered using a direct genetic approach.

Genetic evidence supports a pathogenetic role for LHPP in MDD, perhaps in some sort of functional interaction with HTR1A. Additional attempts to replicate our findings and analysis of LHPP genetic association with other psychiatric diseases are necessary to define the robustness, sensitivity and specificity of the relationship between LHPP and MDD. Our work has not identified a functional polymorphism, and does not even unequivocally identify the product(s) of LHPP involved in MDD. Expression of 10 LHPP transcripts has been detected (Figures 3, 4). All must be considered potentially responsible for the genetic evidence. None are well characterized.

Indeed, little is known about Lhpp, the only certain protein product of an LHPP transcript, beyond its ability to catalyze P-N and P-O bond hydrolysis in vitro. We can only speculate as to the physiological function of Lhpp. It may be a protein histidine or lysine phosphoamidase, that is, an enzyme that modifies the N-linked phosphorylation state of other proteins. Roles for N-linked phosphorylation in prokaryotic signal transduction functions are established,36 but histidine or lysine phosphorylation has been less studied in eukaryotes.37, 38 Since Htr1a is a G-protein-coupled receptor, it is of interest that a G-protein β subunit is one of the few human protein for which a regulatory role of N-linked phosphorylation has been described.39, 40, 41, 42, 43 LHPP does not share meaningful sequence homology with either of the identified human phosphoamidases,44, 45 although these also are not homologous to each other. Among human proteins, Lhpp shares close sequence homology only with Hdhd2, also of undetermined function (Supplementary Figure S1).

EF151005 is selectively expressed in the brain, and hence is a strong candidate to explain the genetic relationship of LHPP to MDD. However, limited linkage disequilibrium between EF151005 exons and the markers linked and associated to MDD (Figure 4) is less supportive of a role for that transcript. This transcript contains two open reading frames of at least 100 amino acids, and neither is homologous to any known functional protein. It is possible, nonetheless, that one or both of these produce a functional protein, that some smaller polypeptide is functional, or that the RNA itself is biologically active. Learning which LHPP product is involved in MDD, and in what manner, if any, it interacts with the Htr1a pathway, are important next steps in fulfilling the potential of this depression gene discovery to lead toward improved treatment through development of novel, targeted therapies.

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Acknowledgements

We thank Drs James P Sullivan, Brian B Spear, Donald N Halbert and Jerry Lanchbury for the guidance and critical review of our work. This work was funded by Abbott Laboratories and Myriad Genetics. We are indebted to the individuals who agreed to participate in this study.

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Correspondence to D Shattuck or D A Katz.

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Supplementary Information accompanies the paper on the Molecular Psychiatry website (http://www.nature.com/mp)

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Neff, C., Abkevich, V., Packer, J. et al. Evidence for HTR1A and LHPP as interacting genetic risk factors in major depression. Mol Psychiatry 14, 621–630 (2009). https://doi.org/10.1038/mp.2008.8

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Keywords

  • genetic linkage
  • genetic association
  • major depression
  • serotonin receptor
  • epistasis

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