Abstract
Objectives
Familial amyloid polyneuropathy (FAP ATTRV30M) shows a wide variation in age‐at‐onset (AO) between clusters, families, and among generations. We will now explore some candidate genes involved in altered disease pathways in order to assess their role as genetic modifiers of AO, using a family‐centered approach.
Methods
We analyzed 62 tagging SNPs from nine genes‐NGAL,MMP‐9,BGN,MEK1,MEK2,ERK1,ERK2,HSP27, and YWHAZ – in a sample of 318 V30M Portuguese patients (106 families), currently under follow‐up. A generalized estimating equation analysis was used to take into account nonindependency of AO between relatives. Also, an in silico analysis was performed in order to assess the functional impact of significant variants associated with AO.
Results
We found for the first time variants from six genes (NGAL,BGN (in the female group), MEK1,MEK2,HSP27, and YWHAZ) that were significantly associated with early‐ and/or late‐onset. Then, we confirmed a strong synergistic interaction between NGAL and MMP‐9 genes. Additionally, by an in silico analysis, we found some variants for MEK1 gene that may alter binding of the transcription factors and that influence the regulation of gene expression regarding microRNA binding sites and splicing regulatory factors.
Interpretation
These findings showed that different genetic factors can modulate differently the onset of disease's symptoms and revealed new mechanisms with clinical implications in the genetic counseling and follow‐up of mutation carriers and could contribute for development of potential therapeutical targets.
Introduction
Familial amyloid polyneuropathy (FAP) ATTRV30M is an autosomal dominantly (AD) systemic amyloidosis with variable clinical presentation, age‐at‐onset (AO), and phenotype severity.1 It is characterized by extracellular amyloid deposits of fibrillary transthyretin (TTR) that results in degeneration of the peripheral nerves and it is caused by a point mutation in the TTR gene (chr18q12.1) (OMIM 176300). More than 100 different mutations have been identified,2 but the Val30Met (V30M) missense mutation is the commonest worldwide.
Typically, a disease of adult‐onset,3 FAP ATTRV30M has not only shown a wide variation in AO between clusters but also within the same focus.4, 5, 6, 7, 8 In Portugal, where it was first described,3 it was characterized as having onset between 25 and 35 years. Nowadays, AO in Portuguese patients varies from 19–82 years.9 However, given the large anticipation detected in Portuguese patients,9 AO variability observed between generations is our target.
Earlier genetic studies focused on some candidate genes that can modify AO of FAP ATTRV30M, using a case–control approach,10, 11 but they did not take into account that early‐ and late‐onset are not separate entities, since they may coexist within the same family.
In our recent study, we used for the first time a family‐centered approach concluding that amyloid P component, serum (APCS) and plasma retinol‐binding protein 4 (RBP4) genes have an important role in AO variation and revealed for the first time the androgen receptor (AR) gene as an AO modifier both in males and females.12
Now, additional candidate genes related with other FAP ATTRV30M signaling pathways were selected. We used the same sample derived from the large Portuguese registry.12
A study using nerve and salivary glands biopsies found that biglycan (BGN), neutrophil gelatinase‐associated lipocalin (NGAL), and matrix metalloproteinase‐9 (MMP‐9) proteins were upregulated in FAP ATTRV30M when compared to controls. BGN seems to be increased in the earliest stages of TTR deposition in the form of nonfibrillar aggregates, whereas NGAL and MMP‐9 were only overexpressed at a later stage of disease progression when fibrillary deposits were formed.13
Monteiro et al., 2006 previously showed that extracellular signal‐regulated kinases 1/2 (ERK1/2) showed increased activation in FAP ATTRV30M salivary gland and nerve biopsies. ERK1/2 kinases (MEK1/2) activation was also upregulated in peripheral nerves, with phosphorylation of ERK1/2. Therefore, this may represent an early signaling cascade leading to cytotoxic effects of TTR aggregates.14
Furthermore, heat shock proteins (HSPs) have been involved in several neurodegenerative diseases including FAP ATTRV30M and an increased expression of heat shock 27 kDa protein 1 (HSP27) related to the presence of extracellular TTR deposition in human FAP nerve, skin, and salivary gland biopsies was found, as compared to controls.15
Moreover, it has been described that tyrosine 3‐monooxygenase/tryptophan 5‐monooxygenase activation protein, zeta (14‐3‐3zeta or YWHAZ) expression levels decreased with aging.16 Also, Vieira et al., 2013 showed that TTR regulates YWHAZ protein levels and so the absence of TTR correlated with decreased levels of YWHAZ in the hippocampus in young/adult TTR null mice when compared to TTR wild‐type animals, although no changes in gene expression were found.17
The aim of our study was to assess for the first time whether variants in these candidate genes have a modifier role in AO variation between generations in FAP ATTRV30M families and to look for a possible interaction between them.
Subjects and Methods
Subjects
From the largest FAP ATTRV30M registry worldwide (at UCA‐CHP, Porto), we collected DNA samples and clinical data concerning 318 patients (106 families). Details are described at length at Santos et al., 2016.12
The study was approved by the Ethics Committee of CHP and all patients gave written informed consent.
DNA extraction
Genomic DNA was extracted from peripheral blood leukocytes, using the standard salting out method18 or from saliva, using ORAGENE kits according to the manufacturer's instructions (DNA Genotek, Inc.).
Selection of SNPs and genotyping
A total of 62 tagging single‐nucleotide polymorphisms (SNPs) were selected (Table 1) with Haploview v.4.1,19 using an r 2 threshold of 0.80 (as measure of linkage disequilibrium) and with a minor allele frequency of 0.10%.
Table 1.
Tagging SNPs selected for each gene
| Candidate genes | ||||||||
|---|---|---|---|---|---|---|---|---|
| NGAL | MMP‐9 | BGN | MEK1 | MEK2 | ERK1 | ERK2 | HSP27 | YWHAZ |
| rs2289860 | ||||||||
| rs350916 | ||||||||
| rs1979013 | ||||||||
| rs1549854 | rs350911 | rs2276008 | rs17365305 | |||||
| rs2266862 | rs745796 | rs10250 | rs13515 | rs4734497 | ||||
| rs1805088 | rs7062216 | rs9672789 | rs2289858 | rs1063311 | rs1376672 | |||
| rs3918249 | rs1126499 | rs1432442 | rs350903 | rs7698 | rs2298432 | rs17365661 | ||
| rs12006030 | rs3918256 | rs2073479 | rs12906411 | rs10412325 | rs1143695 | rs7286558 | rs11769502 | rs7835096 |
| rs3780836 | rs3787268 | rs2269404 | rs16949939 | rs350897 | rs11865086 | rs3827303 | rs3134354 | |
| rs2250889 | rs1042103 | rs11630608 | rs350895 | rs8141815 | rs35083016 | |||
| rs17577 | rs743642 | rs7181936 | rs7258366 | rs9610417 | rs983583 | |||
| rs8039880 | rs350894 | rs5755694 | rs1451637 | |||||
| rs1823059 | ||||||||
| rs12609676 | ||||||||
| rs12459484 | ||||||||
| rs350887 | ||||||||
A multiplex polymerase chain reaction (PCR) amplification for 56 tagging SNPs was performed and genotyping was carried out by a SNaPshot reaction. To genotype rs350911, rs7698, rs983583, and rs1451637, PCR products were digested using TfiI, HinP1I, PsiI, and BfaI restriction enzymes, respectively, and loaded in QIAxcel multicapillary electrophoresis system (Qiagen). The rs12906411 and rs2289858 genotyping was performed by sequencing. Primers’ design and genotyping techniques are described in more detail elsewhere.12
Design and statistical analysis
Our family‐centered approach meant that several members of the same family were included in the analysis; therefore, each patient was “nested” in his/her family. We used generalized estimating equations (GEE),20 since AO is nonindependent between members of the same family. The design and statistical analysis were described elsewhere.12
Results
We present a family‐centered study of variants in nine candidate genes involved in FAP ATTRV30M signaling pathway.
In this study with 318 Portuguese FAP ATTRV30M patients (106 families) with a mean AO of ∼39 years, we unraveled for the first time some polymorphisms associated with AO variation in FAP ATTRV30M, as presented in Table 2. No significant results were found to be associated with AO variation regarding MMP‐9, ERK1, and ERK2 genes (data not shown).
Table 2.
Significant results of the analysis of NGAL, BGN, MEK1, MEK2, HSP27, and YWHAZ SNPs and AO variation taking into account intrafamilial nonindependency
| Gene | SNP | Genotypes | B | 95% CI | P‐value |
|---|---|---|---|---|---|
| NGAL | rs3780836 | CC (reference) | – | – | – |
| CT | −6.07 | [−11.15; −0.98] | 0.019 | ||
| BGN (female group) | rs2269404 | CC (reference) | – | – | – |
| TT | 10.48 | [1.03; 19.93] | 0.030 | ||
| MEK1 | rs8039880 | AA (reference) | – | – | – |
| GG | −7.02 | [−14.03; 0.00] | 0.050 | ||
| rs11630608 | TT (reference) | – | – | – | |
| CC | −12.75 | [−20.98; −4.53] | 0.002 | ||
| CT | −9.38 | [−14.21; −4.55] | P < 0.001 | ||
| rs16949939 | CC (reference) | – | – | – | |
| CT | 26.15 | [14.34; 37.96] | P < 0.001 | ||
| rs745796 | TT (reference) | – | – | – | |
| CC | −10.49 | [−19.50; −1.47] | 0.023 | ||
| MEK2 | rs1823059 | CC (reference) | – | – | – |
| TT | 17.08 | [4.13; 30.03] | 0.010 | ||
| HSP27 | rs11769502 | CC (reference) | – | – | – |
| CT | −6.664 | [−11.30; −2.02] | 0.005 | ||
| YWHAZ | rs17365305 | GG (reference) | – | – | – |
| GA | −6.759 | [−12.97; −0.55] | 0.033 |
B, unstandardized coefficient (estimated quantitative effect of each genotype on AO variation compared with the reference genotype); CI, confidence interval; P‐value, significance level was set to 0.05.
The role of NGAL and BGN genes
In NGAL gene, the CT genotype (P = 0.019) of rs3780836 was significantly associated with an earlier onset corresponding to a decrease of 6 years in mean AO (Table 2). For the other SNP assessed and for the haplotypic analyses, no significant results were found.
Since BGN gene is located in the X chromosome, the analyses were stratified by gender and the genotypic analyses were only performed in the female group.
Regarding the allelic analyses performed in the male patients group, no significant result was found associated with AO (data not shown).
Importantly, in the female group, the TT genotype (P = 0.030) of rs2269404 was significantly associated with a later AO, an increase of 10 years in disease onset (Table 2). In the haplotypic analyses performed for the female group, we found a significant result when the C‐G‐T‐C‐C‐A‐G haplotype is present (P = 0.036) associated with a later onset.
Regarding parental transmission for these genes, no significant differences were found.
MEK1 and MEK2 genes and AO
For MEK1 gene, we found four SNPs significantly associated with AO: the CC genotype (P = 0.002) and the CT genotype (P < 0.001) of rs11630608 and the CC genotype (P = 0.023) of rs745796 were associated with an earlier onset and this variation corresponds from 9 to 13 years in disease onset for these polymorphisms (Table 2). On the other hand, the CT genotype (P < 0.001) of rs16949939 was associated with a mean increase of 26 years in AO (Table 2).
Regarding the MEK2 gene, we found that the TT genotype (P = 0.010) of rs1823059 was associated with a later AO, an increase of 17 years (Table 2).
In the haplotypic analyses, no significant results were found (data not shown).
Concerning parental transmission of the SNPs to the affected children, we found a differential transmission for allele C of rs11630608 and allele C of rs745796 in the MEK1 gene. Nonaffected fathers transmitted more often than expected these alleles that are involved in an earlier onset. In addition, for the rs11630608, sons of non‐affected fathers received more often than expected the C allele (P = 0.012), while for the rs745796, daughters of non‐affected fathers received more often than expected the C allele (P = 0.013) (data not shown).
Regarding MEK2 gene, for the rs1823059, we found that nonaffected fathers transmitted more often than expected the T allele that is associated with a later onset (P = 0.015). For the other SNPs, we did not find any significant differences in parental transmission (data not shown).
HSP27 and YWHAZ genes and AO variation
We found that the CT genotype (P = 0.005) of rs11769502 for HSP27 gene and the GA genotype (P = 0.033) of rs17365305 for YWHAZ gene, were significantly associated with earlier onset and the difference corresponds to a decrease of 7 years in mean AO (Table 2). For these genes, we also performed haplotype‐based analysis, but no differences were found (data not shown).
For these genes, no significant differences were found in parental transmission.
Functional impact and gene–gene interactions
To explore the functional impact of the SNPs associated with AO variation, we performed an in silico analysis using FuncPred and is‐rSNP. Particular attention was paid to rs745796 of MEK1 gene since some SNPs in LD (rs10851759, rs11071895, rs12914079, rs4776791, rs7403574, and rs8043062) may alter transcription factors’ binding (TFB) sites. In addition, the is‐rSNP algorithm highlighted that this SNP may also significantly affect the ability of one transcription factor to bind to DNA (LM120, P = 0.001) (Fig. 1). This analysis also predicts that rs537 (which is in LD with rs745796) may affect microRNA binding sites.
Figure 1.
The sequence logo of the one transcription factor (TF) binding site potentially disrupted by MEK1 rs745796.
Additionally, we found that rs11071896 and rs17851970 (which are in LD with rs11630608 of MEK1), rs1030986 and rs16953566 (which are in LD with rs16949939 of MEK1) may alter the recognition sites for splicing regulatory factors.
A strong synergistic interaction was found with the MDR analysis, as shown in the dendogram (Fig. 2) for the best model, between the rs17577 of the MMP‐9 gene and rs12006030 of the NGAL gene, with a testing balanced accuracy (TBA) of 0.59 and a cross‐validation consistency (CVC) of 10/10. After permutation testing, this model was still significant (P = 0.037).
Figure 2.
Dendogram showing a strong synergistic interaction among neutrophil gelatinase‐associated lipocalin (NGAL)‐MMP‐9 genes (darker lines suggest a synergistic relationship – shorter the lines, stronger the interaction).
Discussion
Research on age‐at‐onset (AO) variation has been central in several dominant diseases including FAP ATTRV30M, since it might lead to a better understanding of the disease pathogenesis mechanisms. Thus, this study addresses the identification of variants of possible candidate genes as AO genetic modifiers in FAP ATTRV30M. To the best of our knowledge, this is the first study that examines the association of these six potential candidate genes (NGAL, BGN, MEK1, MEK2, HSP27, and YWHAZ) linked to several FAP ATTRV30M signaling pathways with AO, using a family‐centered approach.
NGAL and BGN variants associated with AO variation
We examined variants in genes linked to remodeling of the extracellular matrix (ECM)‐related components as NGAL, MMP‐9, and BGN due to its overexpression in FAP ATTRV30M. In our sample, we found that the CT genotype of rs3780836 in the NGAL gene was associated with an earlier onset and we hypothesize that this variant could be a genetic risk factor for the FAP ATTRV30M patients. On the other hand, we found that in the female group, the rare genotype (TT) of rs2269404 of the BGN gene was associated with a later onset, leading us to suggest that this variant can have a possible protective effect in females. We also performed an MDR analysis for detection of gene–gene interaction, which is a powerful statistical tool of multilocus data reduction to improve the detection of genotypic combinations that predict disease risk.21 We found a strong synergistic interaction between NGAL and MMP‐9 genes, confirmed by a 1000‐fold permutation test. In addition, this study confirm the data already described in a previous study, using FAP ATTRV30M nerve and salivary glands biopsies, which showed that NGAL forms a complex with MMP‐9 and where expression of these genes seems to overlap.13 Therefore, this was the first study that explored the possible involvement of the variants of these genes associated with AO variation, using a family‐centered approach. Furthermore, NGAL and MMP‐9 were only overexpressed at a later stage when amyloid fibrils were already present, while BGN was upregulated in the earliest stages of TTR deposition, when nonfibrillar TTR aggregates were already present, but could coexist with TTR fibrils.13 Similarly, Cardoso et al., 2008 corroborated the observations reported for human tissues,13 but using an FAP ATTRV30M transgenic mice model.22
Role of MEK1 and MEK2 variants in AO variability
Although molecular signaling mechanisms in FAP ATTRV30M are not fully understood, a previous study provides evidence for the involvement of the MEK‐ERK MAPK signaling pathway in disease pathogenesis.14 Therefore, we selected MEK1/2 and ERK1/2 as candidate genes due to their role as mediators of the cytotoxic effects of TTR aggregates in different stages of disease progression.
In a study using human FAP ATTRV30M nerve biopsies, MEK1/2 activation was found upregulated in both asymptomatic carriers and patients when compared to controls. Furthermore, phosphorylation levels of MEK1/2 were decreased in later symptomatic stages.14 MEK1/2 is activated after phosphorylation and may lead to ERK1/2 activation in response to a variety of hormones, growth factors, and oxidative stress, which can regulate transcription and translation.23, 24 When ERK signaling cascade is early activated, it can lead to increased cell proliferation and TTR aggregates expression levels. This will lead to cytotoxic effects by TTR aggregates and to an earlier AO.14 Likewise, it was shown in peripheral nerves of a FAP transgenic mouse model an increased ERK1/2 activation when TTR deposits occurs when compared to control animals, where older animals (17 months) had twice the activation of younger ones (2 months).14 Additionally, it was shown a sequential activation of MEK1/2 and ERK1/2 in brains with early stage of neurofibrillary degeneration.23
We found that four variants in MEK1 were associated with an earlier AO and one variant associated with a later disease onset. Interestingly, we found a differential parental transmission regarding rs11630608 and rs745796 in the MEK1 gene where the nonaffected fathers added a genetic risk effect to AO variation. Moreover, sons of nonaffected fathers in the case of rs11630608 and daughters of nonaffected fathers in the case of rs745796 have an increased susceptibility for earlier AO when they receive the rare allele (C). Additionally, we found that the rs1823059 TT genotype of MEK2 was associated with a later AO. Furthermore, for the rs1823059 in the MEK2 nonaffected fathers added a protector genetic effect to AO variation leading to a later AO.
The adverse or protective effects associated with early‐ and late‐onset of MEK1/2 variants point to an effect of these genes in our sample. We also found a possible modulatory effect on AO associated with the noncarrier chromosome (a transacting effect).
In silico analysis revealed some variants in LD with rs745796 of MEK1 gene that may alter binding of the transcription factors LM120 promoting upregulation of this gene. Furthermore, LM120 was predicted to have more affinity when the C allele is present, reinforcing our genotype analysis where the CC genotype was found to be associated with individuals with an earlier AO. As in other studies, this could lead to an early activation of this pathway.23 Additionally, we also found other alterations that could influence the regulation of gene expression regarding microRNA binding sites and splicing regulatory factors. Therefore, the inhibition or activation of the factors involved in the MEK1/2 signaling cascade can be good targets for the development of novel therapeutic approaches.
HSP27 and YWHAZ variants and AO
Several studies have reported the essential role of the heat shock proteins (HSPs) in various neurodegenerative disorders associated with protein aggregation since these are considered important for cellular defense mechanisms. Thus, it was already demonstrated that in the presence of protein misfolding and aggregation, a neuroprotective stress response mediated by HSPs can be induced in Alzheimer's disease (AD),25 Parkinson's disease26, and Huntington's disease.27 However, activation of heat shock transcription factor 1 (HSF) is required for upregulation of the HSP synthesis. In a previous study, it was shown that in FAP ATTRV30M human nerve, skin, and salivary gland biopsies with extracellular TTR deposits, there is induction of intracellular activation of HSF1 and consequently an increase in the expression of HSP27 and HSP70.15
In this study, we selected the HSP27 gene in order to investigate if it influences AO variation, since HSP27 upregulation was only observed in tissues with extracellular TTR deposition.15 We found that rs11769502 of HSP27 was associated with an earlier onset, reinforcing the important role of HSP27 in FAP ATTRV30M. Therefore, the effect of this variant could induce an early neuroprotective intracellular stress response by increasing HSP27 expression, activating the cell defense mechanism to prevent neurodegeneration in FAP ATTRV30M.
As with HSPs, YWHAZ protein might act as a neuroprotection mechanism against toxicity in a variety of neurodegenerative diseases with common cellular and molecular mechanisms including protein aggregation since this may function as a sweeper of misfolded proteins.28 In a previous study in AD, the authors found that YWHAZ stimulates tau phosphorylation29 and is upregulated in the patients’ brains.30 In another study, it was shown the specificity of TTR to regulate YWHAZ levels and decreased YWHAZ protein expression in the hippocampus of young/adult TTR null mice when compared to TTR wild‐type animals.17 Also, it was shown that YWHAZ expression levels decrease with aging.16
We found that rs17365305 of YWHAZ gene was associated with an earlier onset, leading us to suggest that in the presence of this variant, the potential risk effect may be increased and the YWHAZ‐related defense mechanisms blocked. Therefore, the modulation of this variant will be important in order to protect early‐onset patients.
In conclusion, the results of our study provide evidence for an association of DNA noncoding variants of genes in FAP ATTRV30M pathways that may have phenotypic implications, particularly, in AO variation. However, our study does not preclude the possibility that other genes involved in these or other pathways may act as genetic modifiers of AO. Although an in silico analysis has been performed to predict functional impact of significant variants, functional studies will be important to deepen our knowledge. Moreover, in the future, it would also be interesting to replicate our study in other FAP ATTRV30M populations.
Therefore, with this study, we reveal for the first time, using a family‐centered approach, that variants of NGAL, BGN, MEK1, MEK2, HSP27, and YWHAZ may act as potential genetic modulators of AO in FAP ATTRV30M, which could be useful for the development of novel therapeutic approaches, improve patient care, and aid in the genetic counseling of mutation carriers.
Author Contributions
CL, AS: Conception and design of the study. TC, DS, MA‐F, DM, CL, AS: Acquisition and analysis of data. DS, CL, AS: Drafting a significant portion of the manuscript or figures. TC, MA‐F, DM, JS, IA, AS: Critical revision of the manuscript for important intellectual content. DM, CL, AS: Statistical expertize. TC, JS, IA, CL, AS: Obtaining funding. MA‐F, IA, CL: Administrative, technical, or material support. JS, CL, AS: Study supervision.
Conflicts of Interest
D. Santos has received research support from a FCT fellowship (SFRH/BD/91160/2012) and received funding from Pfizer Inc for scientific meeting expenses (travel, accommodations, and registration). T. Coelho's institution has received support from FoldRx Pharmaceuticals, which was acquired by Pfizer Inc in October 2010; T. Coelho has served on the scientific advisory board of Pfizer Inc and received funding from Pfizer Inc for scientific meeting expenses (travel, accommodations, and registration). She currently serves on the THAOS (natural history disease registry) scientific advisory board. M. Alves‐Ferreira has received research support from a FCT fellowship (SFRH/BD/101352/2014) and received funding from Pfizer Inc for scientific meeting expenses (travel, accommodations, and registration). J. Sequeiros, D. Mendonça, I. Alonso, C. Lemos, and A. Sousa report no disclosures.
Acknowledgments
We thank all patients for participating in this study and Vanessa Costa for all the help in assembling family data.
This work was supported by grants of Fundação para a Ciência e Tecnologia, FCT [PTDC/SAU‐GMG/100240/2008 and PEsT], co‐funded by ERDF and COMPETE; and by Financiamento Plurianual de Unidades de Investigação (FCT). DS is the recipient of a FCT fellowship [SFRH/BD/91160/2012].
Our funding sources supported the data collection and study analysis, but did not play a role in the study design, interpretation of data, the writing of the report, and the decision to submit the paper for publication.
References
- 1. Mariani LL, Lozeron P, Theaudin M, et al. Genotype‐phenotype correlation and course of transthyretin familial amyloid polyneuropathies in France. Ann Neurol 2015;78:901–916. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Benson MD. Pathogenesis of transthyretin amyloidosis. Amyloid 2012;19(Suppl 1):14–15. [DOI] [PubMed] [Google Scholar]
- 3. Andrade C. A peculiar form of peripheral neuropathy; familiar atypical generalized amyloidosis with special involvement of the peripheral nerves. Brain 1952;75:408–427. [DOI] [PubMed] [Google Scholar]
- 4. Sousa A, Andersson R, Drugge U, et al. Familial amyloidotic polyneuropathy in Sweden: geographical distribution, age of onset, and prevalence. Hum Hered 1993;43:288–294. [DOI] [PubMed] [Google Scholar]
- 5. Sousa A, Coelho T, Barros J, Sequeiros J. Genetic epidemiology of familial amyloidotic polyneuropathy (FAP)‐type I in Povoa do Varzim and Vila do Conde (north of Portugal). Am J Med Genet 1995;60:512–521. [DOI] [PubMed] [Google Scholar]
- 6. Ikeda S, Nakazato M, Ando Y, Sobue G. Familial transthyretin‐type amyloid polyneuropathy in Japan: clinical and genetic heterogeneity. Neurology 2002;58:1001–1007. [DOI] [PubMed] [Google Scholar]
- 7. Saporta MA, Zaros C, Cruz MW, et al. Penetrance estimation of TTR familial amyloid polyneuropathy (type I) in Brazilian families. Eur J Neurol 2009;16:337–341. [DOI] [PubMed] [Google Scholar]
- 8. Munar‐Ques M, Saraiva MJ, Viader‐Farre C, et al. Genetic epidemiology of familial amyloid polyneuropathy in the Balearic Islands (Spain). Amyloid 2005;12:54–61. [DOI] [PubMed] [Google Scholar]
- 9. Lemos C, Coelho T, Alves‐Ferreira M, et al. Overcoming artefact: anticipation in 284 Portuguese kindreds with familial amyloid polyneuropathy (FAP) ATTRV30M. J Neurol Neurosurg Psychiatry 2014;85:326–330. [DOI] [PubMed] [Google Scholar]
- 10. Soares ML, Coelho T, Sousa A, et al. Susceptibility and modifier genes in Portuguese transthyretin V30M amyloid polyneuropathy: complexity in a single‐gene disease. Hum Mol Genet 2005;14:543–553. [DOI] [PubMed] [Google Scholar]
- 11. Dardiotis E, Koutsou P, Zamba‐Papanicolaou E, et al. Complement C1Q polymorphisms modulate onset in familial amyloidotic polyneuropathy TTR Val30Met. J Neurol Sci 2009;284:158–162. [DOI] [PubMed] [Google Scholar]
- 12. Santos D, Coelho T, Alves‐Ferreira M, et al. Variants in RBP4 and AR genes modulate age at onset in familial amyloid polyneuropathy (FAP ATTRV30M). Eur J Hum Genet 2016;24:755–760. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Sousa MM, do Amaral JB, Guimaraes A, Saraiva MJ. Up‐regulation of the extracellular matrix remodeling genes, biglycan, neutrophil gelatinase‐associated lipocalin, and matrix metalloproteinase‐9 in familial amyloid polyneuropathy. FASEB J 2005;19:124–126. [DOI] [PubMed] [Google Scholar]
- 14. Monteiro FA, Sousa MM, Cardoso I, et al. Activation of ERK1/2 MAP kinases in familial amyloidotic polyneuropathy. J Neurochem 2006;97:151–161. [DOI] [PubMed] [Google Scholar]
- 15. Santos SD, Magalhaes J, Saraiva MJ. Activation of the heat shock response in familial amyloidotic polyneuropathy. J Neuropathol Exp Neurol 2008;67:449–455. [DOI] [PubMed] [Google Scholar]
- 16. VanGuilder HD, Yan H, Farley JA, et al. Aging alters the expression of neurotransmission‐regulating proteins in the hippocampal synaptoproteome. J Neurochem 2010;113:1577–1588. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Vieira M, Saraiva MJ. Transthyretin regulates hippocampal 14‐3‐3zeta protein levels. FEBS Lett 2013;587:1482–1488. [DOI] [PubMed] [Google Scholar]
- 18. Miller SA, Dykes DD, Polesky HF. A simple salting out procedure for extracting DNA from human nucleated cells. Nucleic Acids Res 1988;16:1215. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics 2005;21:263–265. [DOI] [PubMed] [Google Scholar]
- 20. Zeger SL, Liang KY. Longitudinal data analysis for discrete and continuous outcomes. Biometrics 1986;42:121–130. [PubMed] [Google Scholar]
- 21. Motsinger AA, Ritchie MD. Multifactor dimensionality reduction: an analysis strategy for modelling and detecting gene‐gene interactions in human genetics and pharmacogenomics studies. Hum Genomics 2006;2:318–328. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Cardoso I, Brito M, Saraiva MJ. Extracellular matrix markers for disease progression and follow‐up of therapies in familial amyloid polyneuropathy V30M TTR‐related. Dis Markers 2008;25:37–47. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Pei JJ, Braak H, An WL, et al. Up‐regulation of mitogen‐activated protein kinases ERK1/2 and MEK1/2 is associated with the progression of neurofibrillary degeneration in Alzheimer's disease. Brain Res Mol Brain Res 2002;109:45–55. [DOI] [PubMed] [Google Scholar]
- 24. Satoh T, Nakatsuka D, Watanabe Y, et al. Neuroprotection by MAPK/ERK kinase inhibition with U0126 against oxidative stress in a mouse neuronal cell line and rat primary cultured cortical neurons. Neurosci Lett 2000;288:163–166. [DOI] [PubMed] [Google Scholar]
- 25. Wilhelmus MM, Otte‐Holler I, Wesseling P, et al. Specific association of small heat shock proteins with the pathological hallmarks of Alzheimer's disease brains. Neuropathol Appl Neurobiol 2006;32:119–130. [DOI] [PubMed] [Google Scholar]
- 26. Shen HY, He JC, Wang Y, et al. Geldanamycin induces heat shock protein 70 and protects against MPTP‐induced dopaminergic neurotoxicity in mice. J Biol Chem 2005;280:39962–39969. [DOI] [PubMed] [Google Scholar]
- 27. Sittler A, Lurz R, Lueder G, et al. Geldanamycin activates a heat shock response and inhibits huntingtin aggregation in a cell culture model of Huntington's disease. Hum Mol Genet 2001;10:1307–1315. [DOI] [PubMed] [Google Scholar]
- 28. Kaneko K, Hachiya NS. The alternative role of 14‐3‐3 zeta as a sweeper of misfolded proteins in disease conditions. Med Hypotheses 2006;67:169–171. [DOI] [PubMed] [Google Scholar]
- 29. Sluchanko NN, Seit‐Nebi AS, Gusev NB. Phosphorylation of more than one site is required for tight interaction of human tau protein with 14‐3‐3zeta. FEBS Lett 2009;583:2739–2742. [DOI] [PubMed] [Google Scholar]
- 30. Soulie C, Nicole A, Delacourte A, Ceballos‐Picot I. Examination of stress‐related genes in human temporal versus occipital cortex in the course of neurodegeneration: involvement of 14‐3‐3 zeta in this dynamic process. Neurosci Lett 2004;365:1–5. [DOI] [PubMed] [Google Scholar]